Mercurial > repos > bgruening > svm_classifier
changeset 0:4f1b0620ea89 draft
planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit a6e80305ed0892c8163d690a2d376d6b454824de-dirty
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/main_macros.xml Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,341 @@ +<macros> + <token name="@VERSION@">0.9</token> + + <xml name="python_requirements"> + <requirements> + <requirement type="package" version="0.2.1b">eden</requirement> + <yield /> + </requirements> + </xml> + + <xml name="macro_stdio"> + <stdio> + <exit_code range="1:" level="fatal" description="Error occurred. Please check Tool Standard Error" /> + </stdio> + </xml> + + <xml name="train_loadConditional" token_train="tabular" token_data="tabular" token_model="txt"> + <conditional name="selected_tasks"> + <param name="selected_task" type="select" label="Select a Classification Task"> + <option value="load">Load a model and predict</option> + <option value="train" selected="true">Train a model</option> + </param> + <when value="load"> + <param name="infile_model" type="data" format="@MODEL@" label="Models" help="Select a model file." /> + <param name="infile_data" type="data" format="@DATA@" label="Data (tabular)" help="Select the dataset you want to classify."/> + <conditional name="prediction_options"> + <param name="prediction_option" type="select" label="Select the type of prediction"> + <option value="predict">Predict class labels</option> + <option value="advanced">Include advanced options</option> + </param> + <when value="predict"> + </when> + <when value="advanced"> + </when> + </conditional> + </when> + <when value="train"> + <param name="infile_train" type="data" format="@TRAIN@" label="Training samples (tabular)" /> + <conditional name="selected_algorithms"> + <yield /> + </conditional> + </when> + </conditional> + </xml> + + <xml name="advanced_section"> + <section name="options" title="Advanced Options" expanded="False"> + <yield /> + </section> + </xml> + + <xml name="tabular_input"> + <param name="infile" type="data" format="tabular" label="Data file with numeric values"/> + <param name="start_column" type="data_column" data_ref="infile" optional="True" label="Select a subset of data. Start column:" /> + <param name="end_column" type="data_column" data_ref="infile" optional="True" label="End column:" /> + </xml> + + <xml name="tol" token_default_value="0.0" token_help_text="Early stopping heuristics based on the relative center changes. Set to default (0.0) to disable this convergence detection."> + <param argument="tol" type="float" optional="true" value="@DEFAULT_VALUE@" label="Tolerance" help="@HELP_TEXT@"/> + </xml> + + <xml name="n_clusters" token_default_value="8"> + <param argument="n_clusters" type="integer" optional="true" value="@DEFAULT_VALUE@" label="Number of clusters" help=" "/> + </xml> + + <xml name="fit_intercept" token_checked="true"> + <param argument="fit_intercept" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="@CHECKED@" label="Estimate the intercept" help="If false, the data is assumed to be already centered."/> + </xml> + + <xml name="n_iter" token_default_value="5" token_help_text="The number of passes over the training data (aka epochs). "> + <param argument="n_iter" type="integer" optional="true" value="@DEFAULT_VALUE@" label="Number of iterations" help="@HELP_TEXT@"/> + </xml> + + <xml name="shuffle" token_checked="true" token_help_text=" " token_label="Shuffle data after each iteration"> + <param argument="shuffle" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="@CHECKED@" label="@LABEL@" help="@HELP_TEXT@"/> + </xml> + + <xml name="random_state" token_default_value="" token_help_text="Integer number. The seed of the pseudo random number generator to use when shuffling the data. A fixed seed allows reproducible results."> + <param argument="random_state" type="integer" optional="true" value="@DEFAULT_VALUE@" label="Random seed number" help="@HELP_TEXT@"/> + </xml> + + <xml name="warm_start" token_checked="true" token_help_text="When set to True, reuse the solution of the previous call to fit as initialization,otherwise, just erase the previous solution."> + <param argument="warm_start" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="@CHECKED@" label="Perform warm start" help="@HELP_TEXT@"/> + </xml> + + <xml name="C" token_default_value="1.0" token_help_text="Penalty parameter C of the error term."> + <param argument="C" type="float" optional="true" value="@DEFAULT_VALUE@" label="Penalty parameter" help="@HELP_TEXT@"/> + </xml> + + <!--xml name="class_weight" token_default_value="" token_help_text=""> + <param argument="class_weight" type="" optional="true" value="@DEFAULT_VALUE@" label="" help="@HELP_TEXT@"/> + </xml--> + + <xml name="alpha" token_default_value="0.0001" token_help_text="Constant that multiplies the regularization term if regularization is used. "> + <param argument="alpha" type="float" optional="true" value="@DEFAULT_VALUE@" label="Regularization coefficient" help="@HELP_TEXT@"/> + </xml> + + <xml name="n_samples" token_default_value="100" token_help_text="The total number of points equally divided among clusters."> + <param argument="n_samples" type="integer" optional="true" value="@DEFAULT_VALUE@" label="Number of samples" help="@HELP_TEXT@"/> + </xml> + + <xml name="n_features" token_default_value="2" token_help_text="Number of different numerical properties produced for each sample."> + <param argument="n_features" type="integer" optional="true" value="@DEFAULT_VALUE@" label="Number of features" help="@HELP_TEXT@"/> + </xml> + + <xml name="noise" token_default_value="0.0" token_help_text="Floating point number. "> + <param argument="noise" type="float" optional="true" value="@DEFAULT_VALUE@" label="Standard deviation of the Gaussian noise added to the data" help="@HELP_TEXT@"/> + </xml> + + <xml name="C" token_default_value="1.0" token_help_text="Penalty parameter C of the error term. "> + <param argument="C" type="float" optional="true" value="@DEFAULT_VALUE@" label="Penalty parameter" help="@HELP_TEXT@"/> + </xml> + + <xml name="max_iter" token_default_value="300" token_label="Maximum number of iterations per single run" token_help_text=" "> + <param argument="max_iter" type="integer" optional="true" value="@DEFAULT_VALUE@" label="@LABEL@" help="@HELP_TEXT@"/> + </xml> + + <xml name="n_init" token_default_value="10" > + <param argument="n_init" type="integer" optional="true" value="@DEFAULT_VALUE@" label="Number of runs with different centroid seeds" help=" "/> + </xml> + + <xml name="init"> + <param argument="init" type="select" label="Centroid initialization method" help="''k-means++'' selects initial cluster centers that speed up convergence. ''random'' chooses k observations (rows) at random from data as initial centroids."> + <option value="k-means++">k-means++</option> + <option value="random">random</option> + </param> + </xml> + + <xml name="multiple_sparse"> + <repeat name="sparse_inputs" min="1" max="10" title="Inputs"> + <param name="input" type="data" format="txt" label="Sparse matrix file (.mtx, .txt)" help="Specify a sparse matrix file in .txt format."/> + </repeat> + </xml> + + <xml name="eden_citation"> + <citations> + <citation type="bibtex"> + @misc{fabrizio_costa_2015_15094, + author = {Fabrizio Costa and + Björn Grüning and + gigolo}, + title = {EDeN: EDeN - Graph Vectorizer}, + month = feb, + year = 2015, + doi = {10.5281/zenodo.15094}, + url = {http://dx.doi.org/10.5281/zenodo.15094} + } + } + </citation> + </citations> + </xml> + + <xml name="sklearn_citation"> + <citations> + <citation type="bibtex"> + @article{scikit-learn, + title={Scikit-learn: Machine Learning in {P}ython}, + author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V. + and Thirion, B. and Grisel, O. and Blondel, M. and Prettenhofer, P. + and Weiss, R. and Dubourg, V. and Vanderplas, J. and Passos, A. and + Cournapeau, D. and Brucher, M. and Perrot, M. and Duchesnay, E.}, + journal={Journal of Machine Learning Research}, + volume={12}, + pages={2825--2830}, + year={2011} + url = {https://github.com/scikit-learn/scikit-learn} + } + </citation> + </citations> + </xml> + + <xml name="scipy_citation"> + <citations> + <citation type="bibtex"> + @Misc{, + author = {Eric Jones and Travis Oliphant and Pearu Peterson and others}, + title = {{SciPy}: Open source scientific tools for {Python}}, + year = {2001--}, + url = "http://www.scipy.org/", + note = {[Online; accessed 2016-04-09]} + } + </citation> + </citations> + </xml> + + + <xml name="nn_advanced_options"> + <section name="options" title="Advanced Options" expanded="False"> + <yield/> + <param argument="weights" type="select" label="Weight function" help="Used in prediction."> + <option value="uniform" selected="true" help="Uniform weights. All points in each neighborhood are weighted equally.">Uniform</option> + <option value="distance" help="Weight points by the inverse of their distance.">Distance</option> + </param> + <param argument="algorithm" type="select" label="Neighbor selection algorithm" help=" "> + <option value="auto" selected="true">Auto</option> + <option value="ball_tree">BallTree</option> + <option value="kd_tree">KDTree</option> + <option value="brute">Brute-force</option> + </param> + <param argument="leaf_size" type="integer" value="30" label="Leaf size" help="Used with BallTree and KDTree. Affects the time and memory usage of the constructed tree."/> + <!--param name="metric"--> + <!--param name="p"--> + <!--param name="metric_params"--> + </section> + </xml> + + <xml name="svc_advanced_options"> + <section name="options" title="Advanced Options" expanded="False"> + <yield/> + <param argument="kernel" type="select" optional="true" label="Kernel type" help="Kernel type to be used in the algorithm. If none is given, ‘rbf’ will be used."> + <option value="rbf" selected="true">rbf</option> + <option value="linear">linear</option> + <option value="poly">poly</option> + <option value="sigmoid">sigmoid</option> + <option value="precomputed">precomputed</option> + </param> + <param argument="degree" type="integer" optional="true" value="3" label="Degree of the polynomial (polynomial kernel only)" help="Ignored by other kernels. dafault : 3 "/> + <!--TODO: param argument="gamma" float, optional (default=’auto’) --> + <param argument="coef0" type="float" optional="true" value="0.0" label="Zero coefficient (polynomial and sigmoid kernels only)" help="Independent term in kernel function. dafault: 0.0 "/> + <param argument="shrinking" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Use the shrinking heuristic" help=" "/> + <param argument="probability" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="false" label="Enable probability estimates. " help="This must be enabled prior to calling fit, and will slow down that method."/> + <!-- param argument="cache_size"--> + <!--expand macro="class_weight"/--> + <expand macro="tol" default_value="0.001" help_text="Tolerance for stopping criterion. "/> + <expand macro="max_iter" default_value="-1" label="Solver maximum number of iterations" help_text="Hard limit on iterations within solver, or -1 for no limit."/> + <!--param argument="decision_function_shape"--> + <expand macro="random_state" help_text="Integer number. The seed of the pseudo random number generator to use when shuffling the data for probability estimation. A fixed seed allows reproducible results."/> + </section> + </xml> + + <xml name="spectral_clustering_advanced_options"> + <section name="options" title="Advanced Options" expanded="False"> + <expand macro="n_clusters"/> + <param argument="eigen_solver" type="select" value="" label="Eigen solver" help="The eigenvalue decomposition strategy to use."> + <option value="arpack" selected="true">arpack</option> + <option value="lobpcg">lobpcg</option> + <option value="amg">amg</option> + <!--None--> + </param> + <expand macro="random_state"/> + <expand macro="n_init"/> + <param argument="gamma" type="float" optional="true" value="1.0" label="Kernel scaling factor" help="Scaling factor of RBF, polynomial, exponential chi^2 and sigmoid affinity kernel. Ignored for affinity=''nearest_neighbors''."/> + <param argument="affinity" type="select" label="Affinity" help="Affinity kernel to use. "> + <option value="rbf" selected="true">RBF</option> + <option value="precomputed">precomputed</option> + <option value="nearest_neighbors">Nearset neighbors</option> + </param> + <param argument="n_neighbors" type="integer" optional="true" value="10" label="Number of neighbors" help="Number of neighbors to use when constructing the affinity matrix using the nearest neighbors method. Ignored for affinity=''rbf''"/> + <!--param argument="eigen_tol"--> + <param argument="assign_labels" type="select" label="Assign labels" help="The strategy to use to assign labels in the embedding space."> + <option value="kmeans" selected="true">kmeans</option> + <option value="discretize">discretize</option> + </param> + <param argument="degree" type="integer" optional="true" value="3" label="Degree of the polynomial (polynomial kernel only)" help="Ignored by other kernels. dafault : 3 "/> + <param argument="coef0" type="integer" optional="true" value="1" label="Zero coefficient (polynomial and sigmoid kernels only)" help="Ignored by other kernels. dafault : 1 "/> + <!--param argument="kernel_params"--> + </section> + </xml> + + <xml name="minibatch_kmeans_advanced_options"> + <section name="options" title="Advanced Options" expanded="False"> + <expand macro="n_clusters"/> + <expand macro="init"/> + <expand macro="n_init" default_value="3"/> + <expand macro="max_iter" default_value="100"/> + <expand macro="tol" help_text="Early stopping heuristics based on normalized center change. To disable set to 0.0 ."/> + <expand macro="random_state"/> + <param argument="batch_size" type="integer" optional="true" value="100" label="Batch size" help="Size of the mini batches."/> + <!--param argument="compute_labels"--> + <param argument="max_no_improvement" type="integer" optional="true" value="10" label="Maximum number of improvement attempts" help=" + Convergence detection based on inertia (the consecutive number of mini batches that doe not yield an improvement on the smoothed inertia). + To disable, set max_no_improvement to None. "/> + <param argument="init_size" type="integer" optional="true" value="" label="Number of random initialization samples" help="Number of samples to randomly sample for speeding up the initialization . ( default: 3 * batch_size )"/> + <param argument="reassignment_ratio" type="float" optional="true" value="0.01" label="Re-assignment ratio" help="Controls the fraction of the maximum number of counts for a center to be reassigned. Higher values yield better clustering results."/> + </section> + </xml> + + <xml name="kmeans_advanced_options"> + <section name="options" title="Advanced Options" expanded="False"> + <expand macro="n_clusters"/> + <expand macro="init"/> + <expand macro="n_init"/> + <expand macro="max_iter"/> + <expand macro="tol" default_value="0.0001" help_text="Relative tolerance with regards to inertia to declare convergence."/> + <!--param argument="precompute_distances"/--> + <expand macro="random_state"/> + <param argument="copy_x" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Use a copy of data for precomputing distances" help="Mofifying the original data introduces small numerical differences caused by subtracting and then adding the data mean."/> + </section> + </xml> + + <xml name="birch_advanced_options"> + <section name="options" title="Advanced Options" expanded="False"> + <param argument="threshold" type="float" optional="true" value="0.5" label="Subcluster radius threshold" help="The radius of the subcluster obtained by merging a new sample; the closest subcluster should be less than the threshold to avoid a new subcluster."/> + <param argument="branching_factor" type="integer" optional="true" value="50" label="Maximum number of subclusters per branch" help="Maximum number of CF subclusters in each node."/> + <expand macro="n_clusters" default_value="3"/> + <!--param argument="compute_labels"/--> + </section> + </xml> + + <xml name="dbscan_advanced_options"> + <section name="options" title="Advanced Options" expanded="False"> + <param argument="eps" type="float" optional="true" value="0.5" label="Maximum neighborhood distance" help="The maximum distance between two samples for them to be considered as in the same neighborhood."/> + <param argument="min_samples" type="integer" optional="true" value="5" label="Minimal core point density" help="The number of samples (or total weight) in a neighborhood for a point (including the point itself) to be considered as a core point."/> + <param argument="metric" type="text" optional="true" value="euclidean" label="Metric" help="The metric to use when calculating distance between instances in a feature array."/> + <param argument="algorithm" type="select" label="Pointwise distance computation algorithm" help="The algorithm to be used by the NearestNeighbors module to compute pointwise distances and find nearest neighbors."> + <option value="auto" selected="true">auto</option> + <option value="ball_tree">ball_tree</option> + <option value="kd_tree">kd_tree</option> + <option value="brute">brute</option> + </param> + <param argument="leaf_size" type="integer" optional="true" value="30" label="Leaf size" help="Leaf size passed to BallTree or cKDTree. Memory and time efficieny factor in tree constrution and querying."/> + </section> + </xml> + + <xml name="clustering_algorithms_options"> + <conditional name="algorithm_options"> + <param name="selected_algorithm" type="select" label="Clustering Algorithm"> + <option value="KMeans" selected="true">KMeans</option> + <option value="SpectralClustering">Spectral Clustering</option> + <option value="MiniBatchKMeans">Mini Batch KMeans</option> + <option value="DBSCAN">DBSCAN</option> + <option value="Birch">Birch</option> + </param> + <when value="KMeans"> + <expand macro="kmeans_advanced_options"/> + </when> + <when value="DBSCAN"> + <expand macro="dbscan_advanced_options"/> + </when> + <when value="Birch"> + <expand macro="birch_advanced_options"/> + </when> + <when value="SpectralClustering"> + <expand macro="spectral_clustering_advanced_options"/> + </when> + <when value="MiniBatchKMeans"> + <expand macro="minibatch_kmeans_advanced_options"/> + </when> + </conditional> + </xml> +</macros>
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/svm.xml Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,176 @@ +<tool id="svm_classifier" name="Support vector machines (SVMs)" version="@VERSION@"> + <description>for classification</description> + <expand macro="python_requirements"/> + <expand macro="macro_stdio"/> + <macros> + <import>main_macros.xml</import> + <!-- macro name="class_weight" argument="class_weight"--> + </macros> + <version_command>echo "@VERSION@"</version_command> + <command><![CDATA[ + python "$svc_script" '$inputs' +]]> + </command> + <configfiles> + <inputs name="inputs"/> + <configfile name="svc_script"> +<![CDATA[ +import sys +import json +import numpy as np +import sklearn.svm +import pandas +import pickle + +input_json_path = sys.argv[1] +params = json.load(open(input_json_path, "r")) + +#if $selected_tasks.selected_task == "load": + +classifier_object = pickle.load(open("$infile_model", 'r')) + +data = pandas.read_csv("$selected_tasks.infile_data", sep='\t', header=0, index_col=None, parse_dates=True, encoding=None, tupleize_cols=False ) +prediction = classifier_object.predict(data) +prediction_df = pandas.DataFrame(prediction) +res = pandas.concat([data, prediction_df], axis=1) +res.to_csv(path_or_buf = "$outfile", sep="\t", index=False) + +#else: + +data_train = pandas.read_csv("$selected_tasks.infile_train", sep='\t', header=0, index_col=None, parse_dates=True, encoding=None, tupleize_cols=False ) + +data = data_train.ix[:,0:len(data_train.columns)-1] +labels = np.array(data_train[data_train.columns[len(data_train.columns)-1]]) + +options = params["selected_tasks"]["selected_algorithms"]["options"] +selected_algorithm = params["selected_tasks"]["selected_algorithms"]["selected_algorithm"] + +if not(selected_algorithm=="LinearSVC"): + if options["kernel"]: + options["kernel"] = str(options["kernel"]) + +my_class = getattr(sklearn.svm, selected_algorithm) +classifier_object = my_class(**options) +classifier_object.fit(data,labels) + +pickle.dump(classifier_object,open("$outfile", 'w+')) + +#end if + +]]> + </configfile> + </configfiles> + <inputs> + <expand macro="train_loadConditional"> + <param name="selected_algorithm" type="select" label="Classifier type"> + <option value="SVC">C-Support Vector Classification</option> + <option value="NuSVC">Nu-Support Vector Classification</option> + <option value="LinearSVC">Linear Support Vector Classification</option> + </param> + <when value="SVC"> + <expand macro="svc_advanced_options"> + <expand macro="C"/> + </expand> + </when> + <when value="NuSVC"> + <expand macro="svc_advanced_options"> + <param argument="nu" type="float" optional="true" value="0.5" label="Nu control parameter" help="Controls the number of support vectors. Should be in the interval (0, 1]. "/> + </expand> + </when> + <when value="LinearSVC"> + <section name="options" title="Advanced Options" expanded="False"> + <expand macro="C"/> + <expand macro="tol" default_value="0.001" help_text="Tolerance for stopping criterion. "/> + <expand macro="random_state" help_text="Integer number. The seed of the pseudo random number generator to use when shuffling the data for probability estimation. A fixed seed allows reproducible results."/> + <!--expand macro="class_weight"/--> + <param argument="max_iter" type="integer" optional="true" value="1000" label="Maximum number of iterations" help="The maximum number of iterations to be run."/> + <param argument="loss" type="select" label="Loss function" help="Specifies the loss function. ''squared_hinge'' is the square of the hinge loss."> + <option value="squared_hinge" selected="true">Squared hinge</option> + <option value="hinge">Hinge</option> + </param> + <param argument="penalty" type="select" label="Penalization norm" help=" "> + <option value="l1" >l1</option> + <option value="l2" selected="true">l2</option> + </param> + <param argument="dual" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Use the shrinking heuristic" help="Select the algorithm to either solve the dual or primal optimization problem. Prefer dual=False when n_samples > n_features."/> + <param argument="multi_class" type="select" label="Multi-class strategy" help="Determines the multi-class strategy if y contains more than two classes."> + <option value="ovr" selected="true">ovr</option> + <option value="crammer_singer" >crammer_singer</option> + </param> + <param argument="fit_intercept" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Calculate the intercept for this model" help="If set to false, data is expected to be already centered."/> + <param argument="intercept_scaling" type="float" optional="true" value="1" label="Add synthetic feature to the instance vector" help=" "/> + </section> + </when> + </expand> + </inputs> + <outputs> + <data format="txt" name="outfile"/> + </outputs> + <tests> + <test> + <param name="infile_train" value="train_set.tabular" ftype="tabular"/> + <param name="selected_task" value="train"/> + <param name="selected_algorithm" value="SVC"/> + <param name="random_state" value="5"/> + <output name="outfile" file="svc_model01.txt"/> + </test> + <test> + <param name="infile_train" value="train_set.tabular" ftype="tabular"/> + <param name="selected_task" value="train"/> + <param name="selected_algorithm" value="NuSVC"/> + <param name="random_state" value="5"/> + <output name="outfile" file="svc_model02.txt"/> + </test> + <test> + <param name="infile_train" value="train_set.tabular" ftype="tabular"/> + <param name="selected_task" value="train"/> + <param name="selected_algorithm" value="LinearSVC"/> + <param name="random_state" value="5"/> + <output name="outfile" file="svc_model03.txt"/> + </test> + <test> + <param name="infile_model" value="svc_model01.txt" ftype="txt"/> + <param name="infile_data" value="test_set.tabular" ftype="tabular"/> + <param name="selected_task" value="load"/> + <output name="outfile" file="svc_prediction_result01.tabular"/> + </test> + <test> + <param name="infile_model" value="svc_model02.txt" ftype="txt"/> + <param name="infile_data" value="test_set.tabular" ftype="tabular"/> + <param name="selected_task" value="load"/> + <output name="outfile" file="svc_prediction_result02.tabular"/> + </test> + <test> + <param name="infile_model" value="svc_model03.txt" ftype="txt"/> + <param name="infile_data" value="test_set.tabular" ftype="tabular"/> + <param name="selected_task" value="load"/> + <output name="outfile" file="svc_prediction_result03.tabular"/> + </test> + </tests> + <help><![CDATA[ +**What it does** +This module implements the Support Vector Machine (SVM) classification algorithms. +Support vector machines (SVMs) are a set of supervised learning methods used for classification, regression and outliers detection. + +**The advantages of support vector machines are:** + + 1- Effective in high dimensional spaces. + + 2- Still effective in cases where number of dimensions is greater than the number of samples. + + 3- Uses a subset of training points in the decision function (called support vectors), so it is also memory efficient. + + 4- Versatile: different Kernel functions can be specified for the decision function. Common kernels are provided, but it is also possible to specify custom kernels. + +**The disadvantages of support vector machines include:** + + 1- If the number of features is much greater than the number of samples, the method is likely to give poor performances. + + 2- SVMs do not directly provide probability estimates, these are calculated using an expensive five-fold cross-validation + +For more information check http://scikit-learn.org/stable/modules/neighbors.html + + ]]> + </help> + <expand macro="sklearn_citation"/> +</tool> \ No newline at end of file
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/RF01704.fasta Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,4 @@ +>CP000097.1/1411351-1411410 +CAACGUUCACCUCACAUUUGUGAGGCGCAGACAACCCAGGCCAAGGAACGGGGACCUGGA +>ACNY01000002.1/278641-278580 +GAUCGUUCACUUCGCAUCGCGCGAAGCGCAGUUCGCCUCAGGCCAUGGAACGGGGACCUGAG
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result01.txt Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,48 @@ +0 44 64 -76 0 +0 51 48 -73 0 +0 58 65 -49 0 +0 43 61 -49 0 +0 45 43 -79 0 +0 42 60 -98 0 +0 50 55 -59 0 +0 53 53 -56 0 +0 45 44 -61 0 +0 43 65 -84 0 +0 35 52 -75 0 +0 56 56 -70 0 +1 -61 86 43 2 +1 -67 93 15 2 +1 -59 94 36 2 +1 -50 92 62 2 +1 -78 91 70 2 +1 -35 87 47 2 +1 -56 91 52 2 +1 -61 81 46 2 +1 -83 78 34 2 +1 -50 87 45 2 +1 -67 73 50 2 +1 -50 97 45 2 +1 -61 111 45 2 +2 -109 23 -92 1 +2 -94 20 -96 1 +2 -85 26 -88 1 +2 -90 33 -114 1 +2 -63 9 -106 1 +2 -79 9 -93 1 +2 -99 26 -108 1 +2 -81 19 -110 1 +2 -108 21 -108 1 +2 -92 27 -106 1 +2 -88 2 -106 1 +2 -88 15 -103 1 +3 54 -74 4 3 +3 42 -92 31 3 +3 39 -99 -7 3 +3 48 -115 -5 3 +3 39 -96 2 3 +3 31 -109 9 3 +3 33 -96 -8 3 +3 23 -102 4 3 +3 38 -90 21 3 +3 34 -107 1 3 +3 35 -78 18 3
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result02.txt Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,48 @@ +0 44 64 -76 3 +0 51 48 -73 3 +0 58 65 -49 3 +0 43 61 -49 3 +0 45 43 -79 3 +0 42 60 -98 3 +0 50 55 -59 3 +0 53 53 -56 3 +0 45 44 -61 3 +0 43 65 -84 3 +0 35 52 -75 3 +0 56 56 -70 3 +1 -61 86 43 2 +1 -67 93 15 2 +1 -59 94 36 2 +1 -50 92 62 2 +1 -78 91 70 2 +1 -35 87 47 2 +1 -56 91 52 2 +1 -61 81 46 2 +1 -83 78 34 2 +1 -50 87 45 2 +1 -67 73 50 2 +1 -50 97 45 2 +1 -61 111 45 2 +2 -109 23 -92 0 +2 -94 20 -96 0 +2 -85 26 -88 0 +2 -90 33 -114 0 +2 -63 9 -106 0 +2 -79 9 -93 0 +2 -99 26 -108 0 +2 -81 19 -110 0 +2 -108 21 -108 0 +2 -92 27 -106 0 +2 -88 2 -106 0 +2 -88 15 -103 0 +3 54 -74 4 1 +3 42 -92 31 1 +3 39 -99 -7 1 +3 48 -115 -5 1 +3 39 -96 2 1 +3 31 -109 9 1 +3 33 -96 -8 1 +3 23 -102 4 1 +3 38 -90 21 1 +3 34 -107 1 1 +3 35 -78 18 1
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result03.txt Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,48 @@ +0 44 64 -76 -1 +0 51 48 -73 -1 +0 58 65 -49 -1 +0 43 61 -49 -1 +0 45 43 -79 -1 +0 42 60 -98 -1 +0 50 55 -59 -1 +0 53 53 -56 -1 +0 45 44 -61 -1 +0 43 65 -84 -1 +0 35 52 -75 -1 +0 56 56 -70 -1 +1 -61 86 43 -1 +1 -67 93 15 -1 +1 -59 94 36 -1 +1 -50 92 62 -1 +1 -78 91 70 -1 +1 -35 87 47 -1 +1 -56 91 52 -1 +1 -61 81 46 -1 +1 -83 78 34 -1 +1 -50 87 45 -1 +1 -67 73 50 -1 +1 -50 97 45 -1 +1 -61 111 45 -1 +2 -109 23 -92 -1 +2 -94 20 -96 -1 +2 -85 26 -88 -1 +2 -90 33 -114 -1 +2 -63 9 -106 -1 +2 -79 9 -93 -1 +2 -99 26 -108 -1 +2 -81 19 -110 -1 +2 -108 21 -108 -1 +2 -92 27 -106 -1 +2 -88 2 -106 -1 +2 -88 15 -103 -1 +3 54 -74 4 -1 +3 42 -92 31 -1 +3 39 -99 -7 -1 +3 48 -115 -5 -1 +3 39 -96 2 -1 +3 31 -109 9 -1 +3 33 -96 -8 -1 +3 23 -102 4 -1 +3 38 -90 21 -1 +3 34 -107 1 -1 +3 35 -78 18 -1
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result04.txt Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,48 @@ +0 44 64 -76 1 +0 51 48 -73 1 +0 58 65 -49 1 +0 43 61 -49 1 +0 45 43 -79 1 +0 42 60 -98 1 +0 50 55 -59 1 +0 53 53 -56 1 +0 45 44 -61 1 +0 43 65 -84 1 +0 35 52 -75 1 +0 56 56 -70 1 +1 -61 86 43 2 +1 -67 93 15 2 +1 -59 94 36 2 +1 -50 92 62 2 +1 -78 91 70 2 +1 -35 87 47 2 +1 -56 91 52 2 +1 -61 81 46 2 +1 -83 78 34 2 +1 -50 87 45 2 +1 -67 73 50 2 +1 -50 97 45 2 +1 -61 111 45 2 +2 -109 23 -92 3 +2 -94 20 -96 3 +2 -85 26 -88 3 +2 -90 33 -114 3 +2 -63 9 -106 3 +2 -79 9 -93 3 +2 -99 26 -108 3 +2 -81 19 -110 3 +2 -108 21 -108 3 +2 -92 27 -106 3 +2 -88 2 -106 3 +2 -88 15 -103 3 +3 54 -74 4 0 +3 42 -92 31 0 +3 39 -99 -7 0 +3 48 -115 -5 0 +3 39 -96 2 0 +3 31 -109 9 0 +3 33 -96 -8 0 +3 23 -102 4 0 +3 38 -90 21 0 +3 34 -107 1 0 +3 35 -78 18 0
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result05.txt Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,48 @@ +0 44 64 -76 0 +0 51 48 -73 0 +0 58 65 -49 0 +0 43 61 -49 0 +0 45 43 -79 0 +0 42 60 -98 0 +0 50 55 -59 0 +0 53 53 -56 0 +0 45 44 -61 0 +0 43 65 -84 0 +0 35 52 -75 0 +0 56 56 -70 0 +1 -61 86 43 2 +1 -67 93 15 2 +1 -59 94 36 2 +1 -50 92 62 2 +1 -78 91 70 2 +1 -35 87 47 2 +1 -56 91 52 2 +1 -61 81 46 2 +1 -83 78 34 2 +1 -50 87 45 2 +1 -67 73 50 2 +1 -50 97 45 2 +1 -61 111 45 2 +2 -109 23 -92 0 +2 -94 20 -96 0 +2 -85 26 -88 0 +2 -90 33 -114 0 +2 -63 9 -106 0 +2 -79 9 -93 0 +2 -99 26 -108 0 +2 -81 19 -110 0 +2 -108 21 -108 0 +2 -92 27 -106 0 +2 -88 2 -106 0 +2 -88 15 -103 0 +3 54 -74 4 1 +3 42 -92 31 1 +3 39 -99 -7 1 +3 48 -115 -5 1 +3 39 -96 2 1 +3 31 -109 9 1 +3 33 -96 -8 1 +3 23 -102 4 1 +3 38 -90 21 1 +3 34 -107 1 1 +3 35 -78 18 1
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result06.txt Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,48 @@ +0 44 64 -76 0 +0 51 48 -73 0 +0 58 65 -49 0 +0 43 61 -49 0 +0 45 43 -79 0 +0 42 60 -98 0 +0 50 55 -59 0 +0 53 53 -56 0 +0 45 44 -61 0 +0 43 65 -84 0 +0 35 52 -75 0 +0 56 56 -70 0 +1 -61 86 43 1 +1 -67 93 15 1 +1 -59 94 36 1 +1 -50 92 62 1 +1 -78 91 70 1 +1 -35 87 47 1 +1 -56 91 52 1 +1 -61 81 46 1 +1 -83 78 34 1 +1 -50 87 45 1 +1 -67 73 50 1 +1 -50 97 45 1 +1 -61 111 45 1 +2 -109 23 -92 2 +2 -94 20 -96 2 +2 -85 26 -88 2 +2 -90 33 -114 2 +2 -63 9 -106 2 +2 -79 9 -93 2 +2 -99 26 -108 2 +2 -81 19 -110 2 +2 -108 21 -108 2 +2 -92 27 -106 2 +2 -88 2 -106 2 +2 -88 15 -103 2 +3 54 -74 4 3 +3 42 -92 31 3 +3 39 -99 -7 3 +3 48 -115 -5 3 +3 39 -96 2 3 +3 31 -109 9 3 +3 33 -96 -8 3 +3 23 -102 4 3 +3 38 -90 21 3 +3 34 -107 1 3 +3 35 -78 18 3
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result07.txt Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,48 @@ +0 44 64 -76 0 +0 51 48 -73 0 +0 58 65 -49 0 +0 43 61 -49 0 +0 45 43 -79 0 +0 42 60 -98 0 +0 50 55 -59 0 +0 53 53 -56 0 +0 45 44 -61 0 +0 43 65 -84 0 +0 35 52 -75 0 +0 56 56 -70 0 +1 -61 86 43 1 +1 -67 93 15 1 +1 -59 94 36 1 +1 -50 92 62 1 +1 -78 91 70 1 +1 -35 87 47 1 +1 -56 91 52 1 +1 -61 81 46 1 +1 -83 78 34 1 +1 -50 87 45 1 +1 -67 73 50 1 +1 -50 97 45 1 +1 -61 111 45 1 +2 -109 23 -92 2 +2 -94 20 -96 2 +2 -85 26 -88 2 +2 -90 33 -114 2 +2 -63 9 -106 2 +2 -79 9 -93 2 +2 -99 26 -108 2 +2 -81 19 -110 2 +2 -108 21 -108 2 +2 -92 27 -106 2 +2 -88 2 -106 2 +2 -88 15 -103 2 +3 54 -74 4 3 +3 42 -92 31 3 +3 39 -99 -7 3 +3 48 -115 -5 3 +3 39 -96 2 3 +3 31 -109 9 3 +3 33 -96 -8 3 +3 23 -102 4 3 +3 38 -90 21 3 +3 34 -107 1 3 +3 35 -78 18 3
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result08.txt Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,48 @@ +0 44 64 -76 0 +0 51 48 -73 0 +0 58 65 -49 0 +0 43 61 -49 0 +0 45 43 -79 0 +0 42 60 -98 0 +0 50 55 -59 0 +0 53 53 -56 0 +0 45 44 -61 0 +0 43 65 -84 0 +0 35 52 -75 0 +0 56 56 -70 0 +1 -61 86 43 0 +1 -67 93 15 0 +1 -59 94 36 0 +1 -50 92 62 0 +1 -78 91 70 0 +1 -35 87 47 0 +1 -56 91 52 0 +1 -61 81 46 0 +1 -83 78 34 0 +1 -50 87 45 0 +1 -67 73 50 0 +1 -50 97 45 0 +1 -61 111 45 0 +2 -109 23 -92 0 +2 -94 20 -96 0 +2 -85 26 -88 0 +2 -90 33 -114 0 +2 -63 9 -106 0 +2 -79 9 -93 0 +2 -99 26 -108 0 +2 -81 19 -110 0 +2 -108 21 -108 0 +2 -92 27 -106 0 +2 -88 2 -106 0 +2 -88 15 -103 0 +3 54 -74 4 1 +3 42 -92 31 1 +3 39 -99 -7 1 +3 48 -115 -5 1 +3 39 -96 2 1 +3 31 -109 9 1 +3 33 -96 -8 1 +3 23 -102 4 1 +3 38 -90 21 1 +3 34 -107 1 1 +3 35 -78 18 1
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result09.txt Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,48 @@ +0 44 64 -76 0 +0 51 48 -73 0 +0 58 65 -49 0 +0 43 61 -49 0 +0 45 43 -79 0 +0 42 60 -98 0 +0 50 55 -59 0 +0 53 53 -56 0 +0 45 44 -61 0 +0 43 65 -84 0 +0 35 52 -75 0 +0 56 56 -70 0 +1 -61 86 43 0 +1 -67 93 15 0 +1 -59 94 36 0 +1 -50 92 62 0 +1 -78 91 70 0 +1 -35 87 47 0 +1 -56 91 52 0 +1 -61 81 46 0 +1 -83 78 34 0 +1 -50 87 45 0 +1 -67 73 50 0 +1 -50 97 45 0 +1 -61 111 45 0 +2 -109 23 -92 0 +2 -94 20 -96 0 +2 -85 26 -88 0 +2 -90 33 -114 0 +2 -63 9 -106 0 +2 -79 9 -93 0 +2 -99 26 -108 0 +2 -81 19 -110 0 +2 -108 21 -108 0 +2 -92 27 -106 0 +2 -88 2 -106 0 +2 -88 15 -103 0 +3 54 -74 4 1 +3 42 -92 31 1 +3 39 -99 -7 1 +3 48 -115 -5 1 +3 39 -96 2 1 +3 31 -109 9 1 +3 33 -96 -8 1 +3 23 -102 4 1 +3 38 -90 21 1 +3 34 -107 1 1 +3 35 -78 18 1
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result10.txt Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,48 @@ +0 44 64 -76 3 +0 51 48 -73 3 +0 58 65 -49 3 +0 43 61 -49 3 +0 45 43 -79 3 +0 42 60 -98 3 +0 50 55 -59 3 +0 53 53 -56 3 +0 45 44 -61 3 +0 43 65 -84 3 +0 35 52 -75 3 +0 56 56 -70 3 +1 -61 86 43 0 +1 -67 93 15 0 +1 -59 94 36 0 +1 -50 92 62 0 +1 -78 91 70 0 +1 -35 87 47 0 +1 -56 91 52 0 +1 -61 81 46 0 +1 -83 78 34 0 +1 -50 87 45 0 +1 -67 73 50 0 +1 -50 97 45 0 +1 -61 111 45 0 +2 -109 23 -92 2 +2 -94 20 -96 2 +2 -85 26 -88 2 +2 -90 33 -114 2 +2 -63 9 -106 2 +2 -79 9 -93 2 +2 -99 26 -108 2 +2 -81 19 -110 2 +2 -108 21 -108 2 +2 -92 27 -106 2 +2 -88 2 -106 2 +2 -88 15 -103 2 +3 54 -74 4 1 +3 42 -92 31 1 +3 39 -99 -7 1 +3 48 -115 -5 1 +3 39 -96 2 1 +3 31 -109 9 1 +3 33 -96 -8 1 +3 23 -102 4 1 +3 38 -90 21 1 +3 34 -107 1 1 +3 35 -78 18 1
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result11.txt Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,48 @@ +0 44 64 -76 2 +0 51 48 -73 2 +0 58 65 -49 2 +0 43 61 -49 2 +0 45 43 -79 2 +0 42 60 -98 2 +0 50 55 -59 2 +0 53 53 -56 2 +0 45 44 -61 2 +0 43 65 -84 2 +0 35 52 -75 2 +0 56 56 -70 2 +1 -61 86 43 0 +1 -67 93 15 0 +1 -59 94 36 0 +1 -50 92 62 0 +1 -78 91 70 0 +1 -35 87 47 0 +1 -56 91 52 0 +1 -61 81 46 0 +1 -83 78 34 0 +1 -50 87 45 0 +1 -67 73 50 0 +1 -50 97 45 0 +1 -61 111 45 0 +2 -109 23 -92 1 +2 -94 20 -96 1 +2 -85 26 -88 1 +2 -90 33 -114 1 +2 -63 9 -106 1 +2 -79 9 -93 1 +2 -99 26 -108 1 +2 -81 19 -110 1 +2 -108 21 -108 1 +2 -92 27 -106 1 +2 -88 2 -106 1 +2 -88 15 -103 1 +3 54 -74 4 3 +3 42 -92 31 3 +3 39 -99 -7 3 +3 48 -115 -5 3 +3 39 -96 2 3 +3 31 -109 9 3 +3 33 -96 -8 3 +3 23 -102 4 3 +3 38 -90 21 3 +3 34 -107 1 3 +3 35 -78 18 3
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result12.txt Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,48 @@ +0 44 64 -76 1 +0 51 48 -73 1 +0 58 65 -49 1 +0 43 61 -49 0 +0 45 43 -79 1 +0 42 60 -98 1 +0 50 55 -59 1 +0 53 53 -56 1 +0 45 44 -61 0 +0 43 65 -84 1 +0 35 52 -75 1 +0 56 56 -70 1 +1 -61 86 43 2 +1 -67 93 15 1 +1 -59 94 36 1 +1 -50 92 62 0 +1 -78 91 70 1 +1 -35 87 47 1 +1 -56 91 52 0 +1 -61 81 46 2 +1 -83 78 34 1 +1 -50 87 45 0 +1 -67 73 50 1 +1 -50 97 45 0 +1 -61 111 45 1 +2 -109 23 -92 0 +2 -94 20 -96 3 +2 -85 26 -88 3 +2 -90 33 -114 3 +2 -63 9 -106 0 +2 -79 9 -93 1 +2 -99 26 -108 3 +2 -81 19 -110 3 +2 -108 21 -108 3 +2 -92 27 -106 3 +2 -88 2 -106 0 +2 -88 15 -103 3 +3 54 -74 4 1 +3 42 -92 31 3 +3 39 -99 -7 3 +3 48 -115 -5 1 +3 39 -96 2 3 +3 31 -109 9 3 +3 33 -96 -8 3 +3 23 -102 4 3 +3 38 -90 21 3 +3 34 -107 1 3 +3 35 -78 18 3
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result13.txt Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,48 @@ +0 44 64 -76 5 +0 51 48 -73 2 +0 58 65 -49 0 +0 43 61 -49 5 +0 45 43 -79 2 +0 42 60 -98 0 +0 50 55 -59 7 +0 53 53 -56 7 +0 45 44 -61 0 +0 43 65 -84 5 +0 35 52 -75 4 +0 56 56 -70 2 +1 -61 86 43 7 +1 -67 93 15 4 +1 -59 94 36 4 +1 -50 92 62 1 +1 -78 91 70 2 +1 -35 87 47 4 +1 -56 91 52 1 +1 -61 81 46 7 +1 -83 78 34 0 +1 -50 87 45 1 +1 -67 73 50 0 +1 -50 97 45 1 +1 -61 111 45 4 +2 -109 23 -92 4 +2 -94 20 -96 4 +2 -85 26 -88 4 +2 -90 33 -114 3 +2 -63 9 -106 0 +2 -79 9 -93 5 +2 -99 26 -108 3 +2 -81 19 -110 4 +2 -108 21 -108 3 +2 -92 27 -106 3 +2 -88 2 -106 4 +2 -88 15 -103 4 +3 54 -74 4 5 +3 42 -92 31 1 +3 39 -99 -7 4 +3 48 -115 -5 0 +3 39 -96 2 4 +3 31 -109 9 2 +3 33 -96 -8 4 +3 23 -102 4 2 +3 38 -90 21 1 +3 34 -107 1 2 +3 35 -78 18 1
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result14.txt Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,48 @@ +0 44 64 -76 2 +0 51 48 -73 2 +0 58 65 -49 5 +0 43 61 -49 5 +0 45 43 -79 2 +0 42 60 -98 2 +0 50 55 -59 5 +0 53 53 -56 5 +0 45 44 -61 2 +0 43 65 -84 2 +0 35 52 -75 2 +0 56 56 -70 2 +1 -61 86 43 1 +1 -67 93 15 1 +1 -59 94 36 1 +1 -50 92 62 1 +1 -78 91 70 7 +1 -35 87 47 1 +1 -56 91 52 1 +1 -61 81 46 7 +1 -83 78 34 7 +1 -50 87 45 1 +1 -67 73 50 7 +1 -50 97 45 1 +1 -61 111 45 1 +2 -109 23 -92 6 +2 -94 20 -96 6 +2 -85 26 -88 6 +2 -90 33 -114 6 +2 -63 9 -106 3 +2 -79 9 -93 3 +2 -99 26 -108 6 +2 -81 19 -110 6 +2 -108 21 -108 6 +2 -92 27 -106 6 +2 -88 2 -106 3 +2 -88 15 -103 6 +3 54 -74 4 4 +3 42 -92 31 4 +3 39 -99 -7 0 +3 48 -115 -5 0 +3 39 -96 2 0 +3 31 -109 9 0 +3 33 -96 -8 0 +3 23 -102 4 0 +3 38 -90 21 4 +3 34 -107 1 0 +3 35 -78 18 4
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result15.txt Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,48 @@ +0 44 64 -76 1 +0 51 48 -73 1 +0 58 65 -49 1 +0 43 61 -49 1 +0 45 43 -79 1 +0 42 60 -98 1 +0 50 55 -59 1 +0 53 53 -56 1 +0 45 44 -61 1 +0 43 65 -84 1 +0 35 52 -75 1 +0 56 56 -70 1 +1 -61 86 43 2 +1 -67 93 15 2 +1 -59 94 36 2 +1 -50 92 62 2 +1 -78 91 70 2 +1 -35 87 47 2 +1 -56 91 52 2 +1 -61 81 46 2 +1 -83 78 34 2 +1 -50 87 45 2 +1 -67 73 50 2 +1 -50 97 45 2 +1 -61 111 45 2 +2 -109 23 -92 3 +2 -94 20 -96 3 +2 -85 26 -88 3 +2 -90 33 -114 3 +2 -63 9 -106 3 +2 -79 9 -93 3 +2 -99 26 -108 3 +2 -81 19 -110 3 +2 -108 21 -108 3 +2 -92 27 -106 3 +2 -88 2 -106 3 +2 -88 15 -103 3 +3 54 -74 4 0 +3 42 -92 31 0 +3 39 -99 -7 0 +3 48 -115 -5 0 +3 39 -96 2 0 +3 31 -109 9 0 +3 33 -96 -8 0 +3 23 -102 4 0 +3 38 -90 21 0 +3 34 -107 1 0 +3 35 -78 18 0
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result16.txt Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,48 @@ +0 44 64 -76 0 +0 51 48 -73 0 +0 58 65 -49 0 +0 43 61 -49 0 +0 45 43 -79 0 +0 42 60 -98 0 +0 50 55 -59 0 +0 53 53 -56 0 +0 45 44 -61 0 +0 43 65 -84 0 +0 35 52 -75 0 +0 56 56 -70 0 +1 -61 86 43 2 +1 -67 93 15 2 +1 -59 94 36 2 +1 -50 92 62 2 +1 -78 91 70 2 +1 -35 87 47 2 +1 -56 91 52 2 +1 -61 81 46 2 +1 -83 78 34 2 +1 -50 87 45 2 +1 -67 73 50 2 +1 -50 97 45 2 +1 -61 111 45 2 +2 -109 23 -92 3 +2 -94 20 -96 3 +2 -85 26 -88 3 +2 -90 33 -114 3 +2 -63 9 -106 3 +2 -79 9 -93 3 +2 -99 26 -108 3 +2 -81 19 -110 3 +2 -108 21 -108 3 +2 -92 27 -106 3 +2 -88 2 -106 3 +2 -88 15 -103 3 +3 54 -74 4 1 +3 42 -92 31 1 +3 39 -99 -7 1 +3 48 -115 -5 1 +3 39 -96 2 1 +3 31 -109 9 1 +3 33 -96 -8 1 +3 23 -102 4 1 +3 38 -90 21 1 +3 34 -107 1 1 +3 35 -78 18 1
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result17.txt Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,4 @@ +0 +1 +0 +0
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result18.txt Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,4 @@ +-1 +-1 +-1 +-1
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result19.txt Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,4 @@ +0 +1 +0 +0
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result20.txt Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,4 @@ +0 +1 +0 +0
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/cluster_result21.txt Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,4 @@ +0 +1 +0 +0
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/converter_result01.json Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,2 @@ +{"directed": false, "graph": {"info": "RNAfold", "id": "CP000097.1/1411351-1411410", "structure": "....((((.((((((....)))))).)..)))...(((((((..(...)..)).))))).", "sequence": "CAACGUUCACCUCACAUUUGUGAGGCGCAGACAACCCAGGCCAAGGAACGGGGACCUGGA"}, "nodes": [{"position": 0, "id": 0, "label": "C"}, {"position": 1, "id": 1, "label": "A"}, {"position": 2, "id": 2, "label": "A"}, {"position": 3, "id": 3, "label": "C"}, {"position": 4, "id": 4, "label": "G"}, {"position": 5, "id": 5, "label": "U"}, {"position": 6, "id": 6, "label": "U"}, {"position": 7, "id": 7, "label": "C"}, {"position": 8, "id": 8, "label": "A"}, {"position": 9, "id": 9, "label": "C"}, {"position": 10, "id": 10, "label": "C"}, {"position": 11, "id": 11, "label": "U"}, {"position": 12, "id": 12, "label": "C"}, {"position": 13, "id": 13, "label": "A"}, {"position": 14, "id": 14, "label": "C"}, 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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/csc_sparse1.mtx Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,9 @@ +%%MatrixMarket matrix coordinate integer general +% +3 3 6 +1 1 1 +3 1 2 +3 2 3 +1 3 4 +2 3 5 +3 3 6
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/csc_sparse2.mtx Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,9 @@ +%%MatrixMarket matrix coordinate real general +% +3 3 6 +1 1 1.5 +3 1 -2 +3 2 0.3 +1 3 41 +2 3 0.1235 +3 3 6
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/csc_stack_result01.mtx Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,15 @@ +%%MatrixMarket matrix coordinate real general +% +3 6 12 +1 1 1 +3 1 2 +3 2 3 +1 3 4 +2 3 5 +3 3 6 +1 4 1.5 +3 4 -2 +3 5 0.3 +1 6 41 +2 6 0.1235 +3 6 6
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/csr_sparse1.mtx Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,9 @@ +%%MatrixMarket matrix coordinate integer general +% +3 3 6 +1 1 1 +1 3 2 +2 3 3 +3 1 4 +3 2 5 +3 3 6
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/csr_sparse2.mtx Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,9 @@ +%%MatrixMarket matrix coordinate real general +% +3 3 6 +1 1 1 +1 3 -0.2 +2 3 11 +3 1 0.04 +3 2 -5 +3 3 2.6
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/csr_stack_result01.mtx Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,15 @@ +%%MatrixMarket matrix coordinate real general +% +6 3 12 +1 1 1 +1 3 2 +2 3 3 +3 1 4 +3 2 5 +3 3 6 +4 1 1 +4 3 -0.2 +5 3 11 +6 1 0.04 +6 2 -5 +6 3 2.6
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/lda_prediction_result01.tabular Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,5 @@ +3.68258022948 2.82110345641 -3.990140724 -1.9523364774 0 +0.015942057224 -0.711958594347 0.125502976978 -0.972218263337 0 +2.08690768825 0.929399321468 -2.12924084484 -1.99714022188 0 +1.41321052084 0.523750660422 -1.4210539291 -1.49298569451 0 +0.76831404394 1.38267855169 -0.989045048734 0.649504257894 1
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/lda_prediction_result02.tabular Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,5 @@ +3.68258022948 2.82110345641 -3.990140724 -1.9523364774 0 +0.015942057224 -0.711958594347 0.125502976978 -0.972218263337 0 +2.08690768825 0.929399321468 -2.12924084484 -1.99714022188 0 +1.41321052084 0.523750660422 -1.4210539291 -1.49298569451 0 +0.76831404394 1.38267855169 -0.989045048734 0.649504257894 1
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/moons.txt Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,101 @@ +0 1 0 +-0.718349350098 0.695682550603 0 +0.281650649902 -0.195682550603 1 +-0.0960230259077 0.995379112949 0 +-0.871318704123 0.490717552004 0 +-0.623489801859 0.781831482468 0 +-0.0320515775717 0.999486216201 0 +-0.672300890261 0.740277997075 0 +-0.518392568311 0.855142763005 0 +1.15959989503 -0.487181783414 1 +0.222520933956 0.974927912182 0 +1.62348980186 -0.281831482468 1 +0.0 0.5 1 +1.9009688679 0.0661162608824 1 +0.654634945579 -0.43846842205 1 +1.98155915699 0.308841371299 1 +1.22252093396 -0.474927912182 1 +0.840400104967 -0.487181783414 1 +0.949055747011 0.315108218024 0 +-0.838088104892 0.545534901211 0 +0.761445958369 0.648228395308 0 +-0.284527586631 0.958667853037 0 +1.51839256831 -0.355142763005 1 +1.46253829024 -0.386599306373 1 +-0.926916757346 0.375267004879 0 +-0.222520933956 0.974927912182 0 +0.159599895033 0.987181783414 0 +0.0960230259077 0.995379112949 0 +1.83808810489 -0.0455349012105 1 +1.67230089026 -0.240277997075 1 +0.284527586631 0.958667853037 0 +-0.462538290241 0.886599306373 0 +0.926916757346 0.375267004879 0 +0.981559156991 0.191158628701 0 +0.718349350098 0.695682550603 0 +0.00205460724966 0.435929780019 1 +1.57211666012 -0.320172254597 1 +0.903976974092 -0.495379112949 1 +0.376510198141 -0.281831482468 1 +0.032705136961 0.24634541609 1 +0.595216656878 -0.414412623016 1 +1.03205157757 -0.499486216201 1 +0.967948422428 -0.499486216201 1 +0.0990311320976 0.0661162608824 1 +-0.900968867902 0.433883739118 0 +1.09602302591 -0.495379112949 1 +2.0 0.5 1 +0.462538290241 0.886599306373 0 +1.92691675735 0.124732995121 1 +0.327699109739 -0.240277997075 1 +1.0 0.0 0 +0.404783343122 0.914412623016 0 +-0.949055747011 0.315108218024 0 +-0.761445958369 0.648228395308 0 +-0.967294863039 0.25365458391 0 +-0.801413621868 0.598110530491 0 +0.715472413369 -0.458667853037 1 +1.94905574701 0.184891781976 1 +-0.345365054421 0.93846842205 0 +0.777479066044 -0.474927912182 1 +-0.981559156991 0.191158628701 0 +0.073083242654 0.124732995121 1 +1.34536505442 -0.43846842205 1 +1.87131870412 0.00928244799606 1 +1.76144595837 -0.148228395308 1 +0.345365054421 0.93846842205 0 +1.40478334312 -0.414412623016 1 +0.0509442529893 0.184891781976 1 +1.80141362187 -0.0981105304912 1 +0.238554041631 -0.148228395308 1 +0.427883339878 -0.320172254597 1 +-0.991790013823 0.127877161685 0 +-1.0 1.22464679915e-16 0 +0.900968867902 0.433883739118 0 +1.99179001382 0.372122838315 1 +0.161911895108 -0.0455349012105 1 +1.96729486304 0.24634541609 1 +0.672300890261 0.740277997075 0 +0.99794539275 0.0640702199807 0 +-0.404783343122 0.914412623016 0 +0.967294863039 0.25365458391 0 +-0.159599895033 0.987181783414 0 +0.991790013823 0.127877161685 0 +0.838088104892 0.545534901211 0 +0.518392568311 0.855142763005 0 +0.128681295877 0.00928244799606 1 +0.198586378132 -0.0981105304912 1 +0.572116660122 0.820172254597 0 +1.99794539275 0.435929780019 1 +-0.572116660122 0.820172254597 0 +0.623489801859 0.781831482468 0 +0.481607431689 -0.355142763005 1 +0.0184408430089 0.308841371299 1 +0.00820998617675 0.372122838315 1 +0.801413621868 0.598110530491 0 +-0.99794539275 0.0640702199807 0 +1.28452758663 -0.458667853037 1 +1.7183493501 -0.195682550603 1 +0.537461709759 -0.386599306373 1 +0.0320515775717 0.999486216201 0 +0.871318704123 0.490717552004 0
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/nn_model01.txt Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,128 @@ +ccopy_reg +_reconstructor +p0 +(csklearn.neighbors.classification +KNeighborsClassifier +p1 +c__builtin__ +object +p2 +Ntp3 +Rp4 +(dp5 +S'n_neighbors' +p6 +I5 +sS'n_jobs' +p7 +I1 +sS'_y' +p8 +cnumpy.core.multiarray +_reconstruct +p9 +(cnumpy +ndarray +p10 +(I0 +tp11 +S'b' +p12 +tp13 +Rp14 +(I1 +(I48 +tp15 +cnumpy +dtype +p16 +(S'i8' +p17 +I0 +I1 +tp18 +Rp19 +(I3 +S'<' +p20 +NNNI-1 +I-1 +I0 +tp21 +bI00 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+p53 +tp54 +bsb. \ No newline at end of file
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/nn_model02.txt Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,302 @@ +ccopy_reg +_reconstructor +p0 +(csklearn.neighbors.classification +RadiusNeighborsClassifier +p1 +c__builtin__ +object +p2 +Ntp3 +Rp4 +(dp5 +S'n_neighbors' +p6 +NsS'n_jobs' +p7 +I1 +sS'_y' +p8 +cnumpy.core.multiarray +_reconstruct +p9 +(cnumpy +ndarray +p10 +(I0 +tp11 +S'b' +p12 +tp13 +Rp14 +(I1 +(I48 +tp15 +cnumpy +dtype +p16 +(S'i8' +p17 +I0 +I1 +tp18 +Rp19 +(I3 +S'<' +p20 +NNNI-1 +I-1 +I0 +tp21 +bI00 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0/\x00\x00\x00\x00\x00\x00\x004\x00\x00\x00\x00\x00\x00\x00.\x00\x00\x00\x00\x00\x00\x00"\x00\x00\x00\x00\x00\x00\x00-\x00\x00\x00\x00\x00\x00\x002\x00\x00\x00\x00\x00\x00\x00-\x00\x00\x00\x00\x00\x00\x00-\x00\x00\x00\x00\x00\x00\x00\xa4\xff\xff\xff\xff\xff\xff\xff\xa0\xff\xff\xff\xff\xff\xff\xff\xa8\xff\xff\xff\xff\xff\xff\xff\x8e\xff\xff\xff\xff\xff\xff\xff\x96\xff\xff\xff\xff\xff\xff\xff\xa3\xff\xff\xff\xff\xff\xff\xff\x94\xff\xff\xff\xff\xff\xff\xff\x92\xff\xff\xff\xff\xff\xff\xff\x94\xff\xff\xff\xff\xff\xff\xff\x96\xff\xff\xff\xff\xff\xff\xff\x96\xff\xff\xff\xff\xff\xff\xff\x99\xff\xff\xff\xff\xff\xff\xff\x04\x00\x00\x00\x00\x00\x00\x00\x1f\x00\x00\x00\x00\x00\x00\x00\xf9\xff\xff\xff\xff\xff\xff\xff\xfb\xff\xff\xff\xff\xff\xff\xff\x02\x00\x00\x00\x00\x00\x00\x00\t\x00\x00\x00\x00\x00\x00\x00\xf8\xff\xff\xff\xff\xff\xff\xff\x04\x00\x00\x00\x00\x00\x00\x00\x15\x00\x00\x00\x00\x00\x00\x00\x01\x00\x00\x00\x00\x00\x00\x00\x12\x00\x00\x00\x00\x00\x00\x00' +p120 +tp121 +bsb. \ No newline at end of file
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/nn_model03.txt Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,87 @@ +ccopy_reg +_reconstructor +p0 +(csklearn.neighbors.nearest_centroid +NearestCentroid +p1 +c__builtin__ +object +p2 +Ntp3 +Rp4 +(dp5 +S'centroids_' +p6 +cnumpy.core.multiarray +_reconstruct +p7 +(cnumpy +ndarray +p8 +(I0 +tp9 +S'b' +p10 +tp11 +Rp12 +(I1 +(I4 +I4 +tp13 +cnumpy +dtype +p14 +(S'f8' +p15 +I0 +I1 +tp16 +Rp17 +(I3 +S'<' +p18 +NNNI-1 +I-1 +I0 +tp19 +bI00 +S'\x00\x00\x00\x00\x00\x00\x00\x00\xab\xaa\xaa\xaa\xaa\x8aG@\x00\x00\x00\x00\x00\xc0K@UUUUUEQ\xc0\x00\x00\x00\x00\x00\x00\x00@\xab\xaa\xaa\xaa\xaajV\xc0\xab\xaa\xaa\xaa\xaa*3@\x00\x00\x00\x00\x00\xa0Y\xc0\x00\x00\x00\x00\x00\x00\xf0?\xc5N\xec\xc4N\xecM\xc0;\xb1\x13;\xb1SV@\x14;\xb1\x13;\xb1F@\x00\x00\x00\x00\x00\x00\x08@\xe9\xa2\x8b.\xba\xe8B@\x8c.\xba\xe8\xa2\x0bX\xc0t\xd1E\x17]t\x19@' +p20 +tp21 +bsS'metric' +p22 +Veuclidean +p23 +sS'classes_' +p24 +g7 +(g8 +(I0 +tp25 +g10 +tp26 +Rp27 +(I1 +(I4 +tp28 +g14 +(S'i8' +p29 +I0 +I1 +tp30 +Rp31 +(I3 +S'<' +p32 +NNNI-1 +I-1 +I0 +tp33 +bI00 +S'\x00\x00\x00\x00\x00\x00\x00\x00\x01\x00\x00\x00\x00\x00\x00\x00\x02\x00\x00\x00\x00\x00\x00\x00\x03\x00\x00\x00\x00\x00\x00\x00' +p34 +tp35 +bsS'shrink_threshold' +p36 +Nsb. \ No newline at end of file
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/nn_prediction_result01.tabular Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,49 @@ +0 58 56 -67 0 +0 44 64 -76 0 +0 51 48 -73 0 +0 58 65 -49 0 +0 43 61 -49 0 +0 45 43 -79 0 +0 42 60 -98 0 +0 50 55 -59 0 +0 53 53 -56 0 +0 45 44 -61 0 +0 43 65 -84 0 +0 35 52 -75 0 +0 56 56 -70 0 +1 -61 86 43 2 +1 -67 93 15 2 +1 -59 94 36 2 +1 -50 92 62 2 +1 -78 91 70 2 +1 -35 87 47 2 +1 -56 91 52 2 +1 -61 81 46 2 +1 -83 78 34 2 +1 -50 87 45 2 +1 -67 73 50 2 +1 -50 97 45 2 +1 -61 111 45 2 +2 -109 23 -92 1 +2 -94 20 -96 1 +2 -85 26 -88 1 +2 -90 33 -114 1 +2 -63 9 -106 1 +2 -79 9 -93 1 +2 -99 26 -108 1 +2 -81 19 -110 1 +2 -108 21 -108 1 +2 -92 27 -106 1 +2 -88 2 -106 1 +2 -88 15 -103 1 +3 54 -74 4 3 +3 42 -92 31 3 +3 39 -99 -7 3 +3 48 -115 -5 3 +3 39 -96 2 3 +3 31 -109 9 3 +3 33 -96 -8 3 +3 23 -102 4 3 +3 38 -90 21 3 +3 34 -107 1 3 +3 35 -78 18 3
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/nn_prediction_result02.tabular Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,49 @@ +0 58 56 -67 0 +0 44 64 -76 0 +0 51 48 -73 0 +0 58 65 -49 0 +0 43 61 -49 0 +0 45 43 -79 0 +0 42 60 -98 0 +0 50 55 -59 0 +0 53 53 -56 0 +0 45 44 -61 0 +0 43 65 -84 0 +0 35 52 -75 0 +0 56 56 -70 0 +1 -61 86 43 2 +1 -67 93 15 2 +1 -59 94 36 2 +1 -50 92 62 2 +1 -78 91 70 2 +1 -35 87 47 2 +1 -56 91 52 2 +1 -61 81 46 2 +1 -83 78 34 2 +1 -50 87 45 2 +1 -67 73 50 2 +1 -50 97 45 2 +1 -61 111 45 2 +2 -109 23 -92 1 +2 -94 20 -96 1 +2 -85 26 -88 1 +2 -90 33 -114 1 +2 -63 9 -106 1 +2 -79 9 -93 1 +2 -99 26 -108 1 +2 -81 19 -110 1 +2 -108 21 -108 1 +2 -92 27 -106 1 +2 -88 2 -106 1 +2 -88 15 -103 1 +3 54 -74 4 3 +3 42 -92 31 3 +3 39 -99 -7 3 +3 48 -115 -5 3 +3 39 -96 2 3 +3 31 -109 9 3 +3 33 -96 -8 3 +3 23 -102 4 3 +3 38 -90 21 3 +3 34 -107 1 3 +3 35 -78 18 3
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/svc_model01.txt Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,299 @@ +ccopy_reg +_reconstructor +p0 +(csklearn.svm.classes +SVC +p1 +c__builtin__ +object +p2 +Ntp3 +Rp4 +(dp5 +S'_impl' +p6 +S'c_svc' +p7 +sS'kernel' +p8 +S'rbf' +p9 +sS'verbose' +p10 +I00 +sS'probability' +p11 +I00 +sS'classes_' +p12 +cnumpy.core.multiarray +_reconstruct +p13 +(cnumpy +ndarray +p14 +(I0 +tp15 +S'b' +p16 +tp17 +Rp18 +(I1 +(I4 +tp19 +cnumpy +dtype +p20 +(S'i8' +p21 +I0 +I1 +tp22 +Rp23 +(I3 +S'<' +p24 +NNNI-1 +I-1 +I0 +tp25 +bI00 +S'\x00\x00\x00\x00\x00\x00\x00\x00\x01\x00\x00\x00\x00\x00\x00\x00\x02\x00\x00\x00\x00\x00\x00\x00\x03\x00\x00\x00\x00\x00\x00\x00' +p26 +tp27 +bsS'support_' +p28 +g13 +(g14 +(I0 +tp29 +g16 +tp30 +Rp31 +(I1 +(I48 +tp32 +g20 +(S'i4' +p33 +I0 +I1 +tp34 +Rp35 +(I3 +S'<' +p36 +NNNI-1 +I-1 +I0 +tp37 +bI00 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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/svc_model02.txt Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,299 @@ +ccopy_reg +_reconstructor +p0 +(csklearn.svm.classes +NuSVC +p1 +c__builtin__ +object +p2 +Ntp3 +Rp4 +(dp5 +S'_impl' +p6 +S'nu_svc' +p7 +sS'kernel' +p8 +S'rbf' +p9 +sS'verbose' +p10 +I00 +sS'probability' +p11 +I00 +sS'classes_' +p12 +cnumpy.core.multiarray +_reconstruct +p13 +(cnumpy +ndarray +p14 +(I0 +tp15 +S'b' +p16 +tp17 +Rp18 +(I1 +(I4 +tp19 +cnumpy +dtype +p20 +(S'i8' +p21 +I0 +I1 +tp22 +Rp23 +(I3 +S'<' +p24 +NNNI-1 +I-1 +I0 +tp25 +bI00 +S'\x00\x00\x00\x00\x00\x00\x00\x00\x01\x00\x00\x00\x00\x00\x00\x00\x02\x00\x00\x00\x00\x00\x00\x00\x03\x00\x00\x00\x00\x00\x00\x00' +p26 +tp27 +bsS'support_' +p28 +g13 +(g14 +(I0 +tp29 +g16 +tp30 +Rp31 +(I1 +(I48 +tp32 +g20 +(S'i4' +p33 +I0 +I1 +tp34 +Rp35 +(I3 +S'<' +p36 +NNNI-1 +I-1 +I0 +tp37 +bI00 +S'\x00\x00\x00\x00\x01\x00\x00\x00\x02\x00\x00\x00\x03\x00\x00\x00\x04\x00\x00\x00\x05\x00\x00\x00\x06\x00\x00\x00\x07\x00\x00\x00\x08\x00\x00\x00\t\x00\x00\x00\n\x00\x00\x00\x0b\x00\x00\x00\x19\x00\x00\x00\x1a\x00\x00\x00\x1b\x00\x00\x00\x1c\x00\x00\x00\x1d\x00\x00\x00\x1e\x00\x00\x00\x1f\x00\x00\x00 \x00\x00\x00!\x00\x00\x00"\x00\x00\x00#\x00\x00\x00$\x00\x00\x00\x0c\x00\x00\x00\r\x00\x00\x00\x0e\x00\x00\x00\x0f\x00\x00\x00\x10\x00\x00\x00\x11\x00\x00\x00\x12\x00\x00\x00\x13\x00\x00\x00\x14\x00\x00\x00\x15\x00\x00\x00\x16\x00\x00\x00\x17\x00\x00\x00\x18\x00\x00\x00%\x00\x00\x00&\x00\x00\x00\'\x00\x00\x00(\x00\x00\x00)\x00\x00\x00*\x00\x00\x00+\x00\x00\x00,\x00\x00\x00-\x00\x00\x00.\x00\x00\x00/\x00\x00\x00' +p38 +tp39 +bsS'dual_coef_' +p40 +g13 +(g14 +(I0 +tp41 +g16 +tp42 +Rp43 +(I1 +(I3 +I48 +tp44 +g20 +(S'f8' +p45 +I0 +I1 +tp46 +Rp47 +(I3 +S'<' +p48 +NNNI-1 +I-1 +I0 +tp49 +bI00 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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/svc_model03.txt Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,159 @@ +ccopy_reg +_reconstructor +p0 +(csklearn.svm.classes +LinearSVC +p1 +c__builtin__ +object +p2 +Ntp3 +Rp4 +(dp5 +S'loss' +p6 +Vsquared_hinge +p7 +sS'C' +p8 +F1.0 +sS'classes_' +p9 +cnumpy.core.multiarray +_reconstruct +p10 +(cnumpy +ndarray +p11 +(I0 +tp12 +S'b' +p13 +tp14 +Rp15 +(I1 +(I4 +tp16 +cnumpy +dtype +p17 +(S'i8' +p18 +I0 +I1 +tp19 +Rp20 +(I3 +S'<' +p21 +NNNI-1 +I-1 +I0 +tp22 +bI00 +S'\x00\x00\x00\x00\x00\x00\x00\x00\x01\x00\x00\x00\x00\x00\x00\x00\x02\x00\x00\x00\x00\x00\x00\x00\x03\x00\x00\x00\x00\x00\x00\x00' +p23 +tp24 +bsS'verbose' +p25 +I0 +sS'intercept_scaling' +p26 +F1.0 +sS'dual' +p27 +I01 +sS'fit_intercept' +p28 +I01 +sS'max_iter' +p29 +I1000 +sS'n_iter_' +p30 +cnumpy.core.multiarray +scalar +p31 +(g17 +(S'i4' +p32 +I0 +I1 +tp33 +Rp34 +(I3 +S'<' +p35 +NNNI-1 +I-1 +I0 +tp36 +bS'\xe8\x03\x00\x00' +p37 +tp38 +Rp39 +sS'penalty' +p40 +Vl2 +p41 +sS'multi_class' +p42 +Vovr +p43 +sS'random_state' +p44 +I5 +sS'tol' +p45 +F0.001 +sS'coef_' +p46 +g10 +(g11 +(I0 +tp47 +g13 +tp48 +Rp49 +(I1 +(I4 +I4 +tp50 +g17 +(S'f8' +p51 +I0 +I1 +tp52 +Rp53 +(I3 +S'<' +p54 +NNNI-1 +I-1 +I0 +tp55 +bI01 +S'@@\xae\xfaP\xc8\xd4\xbf\xe8\x9b\x9e\x13"\xd6\xdb\xbf\xba\xc8\xd0f\xd1\xb9`\xbf\xca\xa9\x1a\xa8\x93\xda&\xbfv\xa2{\x1d\n\x8e\x95?\x1a\xb3\xc3\x80`\x9fn\xbf\xa5E?\x1dKV\x88\xbf\xb4]v\x97t8f?~R\x8dH\xd4\x9c\x89?+\xe8\xb4\x8b\xe7N\x7f\xbf\xdef\x84\xc2\xaa\xbc\x8e?\xc7\x193\xe1OO\x90\xbf\xc6UW_\x17\xdd\x87\xbf\xed\xa5\x82\x11Xbh?\x9b5w\xe8\x7fR\x9d?\xff\x9fao\xeaB|?' +p56 +tp57 +bsS'intercept_' +p58 +g10 +(g11 +(I0 +tp59 +g13 +tp60 +Rp61 +(I1 +(I4 +tp62 +g53 +I00 +S'\x9e\x05)W2\xcf\xc3\xbf\x98\xa4\x94\x94\x06\xf1\xd1\xbf\x1b<a=\xfb\x89S\xbf[\x9e>\x89\xb1<4\xbf' +p63 +tp64 +bsS'class_weight' +p65 +Nsb. \ No newline at end of file
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/svc_prediction_result01.tabular Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,49 @@ +0 58 56 -67 0 +0 44 64 -76 0 +0 51 48 -73 0 +0 58 65 -49 0 +0 43 61 -49 0 +0 45 43 -79 0 +0 42 60 -98 0 +0 50 55 -59 0 +0 53 53 -56 0 +0 45 44 -61 0 +0 43 65 -84 0 +0 35 52 -75 0 +0 56 56 -70 0 +1 -61 86 43 2 +1 -67 93 15 2 +1 -59 94 36 2 +1 -50 92 62 2 +1 -78 91 70 2 +1 -35 87 47 2 +1 -56 91 52 2 +1 -61 81 46 2 +1 -83 78 34 2 +1 -50 87 45 2 +1 -67 73 50 2 +1 -50 97 45 2 +1 -61 111 45 2 +2 -109 23 -92 1 +2 -94 20 -96 1 +2 -85 26 -88 1 +2 -90 33 -114 1 +2 -63 9 -106 1 +2 -79 9 -93 1 +2 -99 26 -108 1 +2 -81 19 -110 1 +2 -108 21 -108 1 +2 -92 27 -106 1 +2 -88 2 -106 1 +2 -88 15 -103 1 +3 54 -74 4 3 +3 42 -92 31 3 +3 39 -99 -7 3 +3 48 -115 -5 3 +3 39 -96 2 3 +3 31 -109 9 3 +3 33 -96 -8 3 +3 23 -102 4 3 +3 38 -90 21 3 +3 34 -107 1 3 +3 35 -78 18 3
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/svc_prediction_result02.tabular Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,49 @@ +0 58 56 -67 0 +0 44 64 -76 0 +0 51 48 -73 0 +0 58 65 -49 0 +0 43 61 -49 0 +0 45 43 -79 0 +0 42 60 -98 0 +0 50 55 -59 0 +0 53 53 -56 0 +0 45 44 -61 0 +0 43 65 -84 0 +0 35 52 -75 0 +0 56 56 -70 0 +1 -61 86 43 2 +1 -67 93 15 2 +1 -59 94 36 2 +1 -50 92 62 2 +1 -78 91 70 2 +1 -35 87 47 2 +1 -56 91 52 2 +1 -61 81 46 2 +1 -83 78 34 2 +1 -50 87 45 2 +1 -67 73 50 2 +1 -50 97 45 2 +1 -61 111 45 2 +2 -109 23 -92 1 +2 -94 20 -96 1 +2 -85 26 -88 1 +2 -90 33 -114 1 +2 -63 9 -106 1 +2 -79 9 -93 1 +2 -99 26 -108 1 +2 -81 19 -110 1 +2 -108 21 -108 1 +2 -92 27 -106 1 +2 -88 2 -106 1 +2 -88 15 -103 1 +3 54 -74 4 3 +3 42 -92 31 3 +3 39 -99 -7 3 +3 48 -115 -5 3 +3 39 -96 2 3 +3 31 -109 9 3 +3 33 -96 -8 3 +3 23 -102 4 3 +3 38 -90 21 3 +3 34 -107 1 3 +3 35 -78 18 3
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/svc_prediction_result03.tabular Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,49 @@ +0 58 56 -67 0 +0 44 64 -76 0 +0 51 48 -73 0 +0 58 65 -49 0 +0 43 61 -49 0 +0 45 43 -79 0 +0 42 60 -98 0 +0 50 55 -59 0 +0 53 53 -56 0 +0 45 44 -61 0 +0 43 65 -84 0 +0 35 52 -75 0 +0 56 56 -70 0 +1 -61 86 43 2 +1 -67 93 15 2 +1 -59 94 36 2 +1 -50 92 62 2 +1 -78 91 70 2 +1 -35 87 47 2 +1 -56 91 52 2 +1 -61 81 46 2 +1 -83 78 34 2 +1 -50 87 45 2 +1 -67 73 50 2 +1 -50 97 45 2 +1 -61 111 45 2 +2 -109 23 -92 2 +2 -94 20 -96 3 +2 -85 26 -88 2 +2 -90 33 -114 0 +2 -63 9 -106 0 +2 -79 9 -93 3 +2 -99 26 -108 1 +2 -81 19 -110 0 +2 -108 21 -108 1 +2 -92 27 -106 0 +2 -88 2 -106 3 +2 -88 15 -103 3 +3 54 -74 4 3 +3 42 -92 31 3 +3 39 -99 -7 3 +3 48 -115 -5 3 +3 39 -96 2 3 +3 31 -109 9 3 +3 33 -96 -8 3 +3 23 -102 4 3 +3 38 -90 21 3 +3 34 -107 1 3 +3 35 -78 18 3
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/swiss_r.txt Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,101 @@ +0 1 2 0 +-9.02243256039 16.3440735244 -3.91158679019 9.83385989955 +3.63249892241 16.3715663708 6.37347946891 7.33595862597 +-6.59990374868 12.8168912174 5.68894891724 8.71337301364 +12.6005826994 6.48900731901 1.36421345798 12.6742164541 +0.211487814316 14.6524330578 -4.75215950419 4.75686315221 +5.33691943034 18.0519842103 -2.41562073899 5.85815095065 +0.424440090632 13.1317989129 -11.0258838101 11.0340501713 +12.4648244371 20.6305644218 -0.880263861039 12.4958678255 +5.76317738541 20.5065026673 -1.67200654934 6.00081823394 +-7.69903426446 3.50057675518 -6.58731737524 10.132515917 +11.2027859032 0.486740866046 6.81511168671 13.1129004913 +6.15412671259 3.37563551865 2.60836155376 6.68407253026 +6.35942079066 19.3934333304 1.1301790428 6.45906629951 +4.89011222064 20.0245468475 -2.99390399146 5.73381710909 +5.95327096921 4.43054679309 3.25076997787 6.78298906691 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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test.tabular Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,5 @@ +3.68258022948 2.82110345641 -3.990140724 -1.9523364774 +0.015942057224 -0.711958594347 0.125502976978 -0.972218263337 +2.08690768825 0.929399321468 -2.12924084484 -1.99714022188 +1.41321052084 0.523750660422 -1.4210539291 -1.49298569451 +0.76831404394 1.38267855169 -0.989045048734 0.649504257894
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test_set.tabular Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,49 @@ +0 58 56 -67 +0 44 64 -76 +0 51 48 -73 +0 58 65 -49 +0 43 61 -49 +0 45 43 -79 +0 42 60 -98 +0 50 55 -59 +0 53 53 -56 +0 45 44 -61 +0 43 65 -84 +0 35 52 -75 +0 56 56 -70 +1 -61 86 43 +1 -67 93 15 +1 -59 94 36 +1 -50 92 62 +1 -78 91 70 +1 -35 87 47 +1 -56 91 52 +1 -61 81 46 +1 -83 78 34 +1 -50 87 45 +1 -67 73 50 +1 -50 97 45 +1 -61 111 45 +2 -109 23 -92 +2 -94 20 -96 +2 -85 26 -88 +2 -90 33 -114 +2 -63 9 -106 +2 -79 9 -93 +2 -99 26 -108 +2 -81 19 -110 +2 -108 21 -108 +2 -92 27 -106 +2 -88 2 -106 +2 -88 15 -103 +3 54 -74 4 +3 42 -92 31 +3 39 -99 -7 +3 48 -115 -5 +3 39 -96 2 +3 31 -109 9 +3 33 -96 -8 +3 23 -102 4 +3 38 -90 21 +3 34 -107 1 +3 35 -78 18
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/train.tabular Mon May 02 16:15:51 2016 -0400 @@ -0,0 +1,15 @@ +-0.409899987374 -0.649450145317 0.510268556953 -0.229110484125 0 +-1.10383560019 0.0611191480175 1.01725565283 1.79193066057 0 +-0.41009731911 0.731046118333 0.238276079462 1.60843479815 1 +1.48390157074 2.30714564103 -1.83858336229 0.770904924566 1 +0.74006063964 1.38952620136 -0.96404935579 0.702401167325 1 +0.331307031883 1.10808437795 -0.527405721679 0.961279646112 1 +-1.4627878344 -0.343655746393 1.43177660405 1.80949467985 0 +-1.33544682955 -2.24827087098 1.6885444678 -0.922608257112 0 +-0.0417384245742 0.906486336146 -0.13980113811 1.27108242642 1 +-2.73189476502 -1.46239633785 2.83576394706 2.28732123255 0 +-0.300256196558 -0.305034204892 0.340123288396 0.0593443810367 0 +-0.523654501136 -0.426496596688 0.572385315213 0.243891110892 0 +-0.00757221265553 -0.254805682403 0.0572980350837 -0.327374762308 0 +-1.87242461384 -0.413385894664 1.82750303608 2.35149919802 1 +-0.168117705611 -0.811895938369 0.316838713275 -0.819986910541 0
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