changeset 0:4f1b0620ea89 draft

planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit a6e80305ed0892c8163d690a2d376d6b454824de-dirty
author bgruening
date Mon, 02 May 2016 16:15:51 -0400
parents
children a43963a460fb
files main_macros.xml svm.xml test-data/RF01704.fasta test-data/blobs.txt test-data/circles.txt test-data/class.txt test-data/cluster_result01.txt test-data/cluster_result02.txt test-data/cluster_result03.txt test-data/cluster_result04.txt test-data/cluster_result05.txt test-data/cluster_result06.txt test-data/cluster_result07.txt test-data/cluster_result08.txt test-data/cluster_result09.txt test-data/cluster_result10.txt test-data/cluster_result11.txt test-data/cluster_result12.txt test-data/cluster_result13.txt test-data/cluster_result14.txt test-data/cluster_result15.txt test-data/cluster_result16.txt test-data/cluster_result17.txt test-data/cluster_result18.txt test-data/cluster_result19.txt test-data/cluster_result20.txt test-data/cluster_result21.txt test-data/converter_result01.json test-data/converter_result02.json test-data/csc_sparse1.mtx test-data/csc_sparse2.mtx test-data/csc_stack_result01.mtx test-data/csr_sparse1.mtx test-data/csr_sparse2.mtx test-data/csr_stack_result01.mtx test-data/empty_file.txt test-data/friedman1.txt test-data/friedman2.txt test-data/friedman3.txt test-data/gaus.txt test-data/hastie.txt test-data/lda_model01 test-data/lda_model02 test-data/lda_prediction_result01.tabular test-data/lda_prediction_result02.tabular test-data/moons.txt test-data/nn_model01.txt test-data/nn_model02.txt test-data/nn_model03.txt test-data/nn_prediction_result01.tabular test-data/nn_prediction_result02.tabular test-data/nn_prediction_result03.tabular test-data/numeric_values.tabular test-data/qda_model01 test-data/qda_prediction_result01.tabular test-data/regression.txt test-data/scurve.txt test-data/sparse.mtx test-data/sparse_u.txt test-data/svc_model01.txt test-data/svc_model02.txt test-data/svc_model03.txt test-data/svc_prediction_result01.tabular test-data/svc_prediction_result02.tabular test-data/svc_prediction_result03.tabular test-data/swiss_r.txt test-data/test.tabular test-data/test_set.tabular test-data/train.tabular test-data/train_set.tabular test-data/vectorizer_result01.mtx test-data/vectorizer_result02.mtx test-data/vectorizer_result03.mtx test-data/vectorizer_result04.mtx
diffstat 73 files changed, 43632 insertions(+), 0 deletions(-) [+]
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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
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/blobs.txt	Mon May 02 16:15:51 2016 -0400
@@ -0,0 +1,101 @@
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/circles.txt	Mon May 02 16:15:51 2016 -0400
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/class.txt	Mon May 02 16:15:51 2016 -0400
@@ -0,0 +1,101 @@
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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
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--- /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 @@
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--- /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 @@
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--- /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 @@
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--- /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 @@
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--- /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 @@
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--- /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 @@
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--- /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 @@
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--- /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 @@
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--- /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 @@
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--- /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 @@
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--- /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 @@
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--- /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 @@
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--- /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 @@
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--- /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 @@
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--- /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 @@
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--- /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
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--- /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 @@
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--- /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 @@
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--- /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 @@
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--- /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 @@
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--- /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 @@
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/converter_result02.json	Mon May 02 16:15:51 2016 -0400
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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
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/friedman1.txt	Mon May 02 16:15:51 2016 -0400
@@ -0,0 +1,101 @@
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/friedman2.txt	Mon May 02 16:15:51 2016 -0400
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/friedman3.txt	Mon May 02 16:15:51 2016 -0400
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/hastie.txt	Mon May 02 16:15:51 2016 -0400
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Binary file test-data/lda_model02 has changed
--- /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
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--- /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
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/moons.txt	Mon May 02 16:15:51 2016 -0400
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--- /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 @@
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+p53
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\ 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 @@
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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
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/nn_prediction_result03.tabular	Mon May 02 16:15:51 2016 -0400
@@ -0,0 +1,49 @@
+0	58	56	-67	0
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+0	43	61	-49	0
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+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/numeric_values.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
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+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
Binary file test-data/qda_model01 has changed
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/qda_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/regression.txt	Mon May 02 16:15:51 2016 -0400
@@ -0,0 +1,101 @@
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/scurve.txt	Mon May 02 16:15:51 2016 -0400
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/sparse.mtx	Mon May 02 16:15:51 2016 -0400
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/sparse_u.txt	Mon May 02 16:15:51 2016 -0400
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+++ b/test-data/svc_model01.txt	Mon May 02 16:15:51 2016 -0400
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\ No newline at end of file
--- /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 @@
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\xc0\x00\x00\x00\x00\x00\x00\x08@\x00\x00\x00\x00\x00\x007@\x00\x00\x00\x00\x00\x80Y\xc0\x00\x00\x00\x00\x00\x00\x10@\x00\x00\x00\x00\x00\x00\x08@\x00\x00\x00\x00\x00\x00C@\x00\x00\x00\x00\x00\x80V\xc0\x00\x00\x00\x00\x00\x005@\x00\x00\x00\x00\x00\x00\x08@\x00\x00\x00\x00\x00\x00A@\x00\x00\x00\x00\x00\xc0Z\xc0\x00\x00\x00\x00\x00\x00\xf0?\x00\x00\x00\x00\x00\x00\x08@\x00\x00\x00\x00\x00\x80A@\x00\x00\x00\x00\x00\x80S\xc0\x00\x00\x00\x00\x00\x002@'
+p89
+tp90
+bsS'_dual_coef_'
+p91
+g43
+sS'degree'
+p92
+I3
+sS'epsilon'
+p93
+F0.0
+sS'max_iter'
+p94
+I-1
+sS'decision_function_shape'
+p95
+NsS'fit_status_'
+p96
+I0
+sS'_intercept_'
+p97
+g13
+(g14
+(I0
+tp98
+g16
+tp99
+Rp100
+(I1
+(I6
+tp101
+g47
+I00
+S'j\xec(!}<6\xbfB\x9f\x1676\xa5\xa4\xbf\x8a%}\xfa\x91\x16\xa6?\xe4\x0e\x0f2\xd9x\xa4\xbf]\xf9\xf5]\xe3B\xa6?\xb8\x01<N`T\xb5?'
+p102
+tp103
+bsS'intercept_'
+p104
+g13
+(g14
+(I0
+tp105
+g16
+tp106
+Rp107
+(I1
+(I6
+tp108
+g47
+I00
+S'j\xec(!}<6\xbfB\x9f\x1676\xa5\xa4\xbf\x8a%}\xfa\x91\x16\xa6?\xe4\x0e\x0f2\xd9x\xa4\xbf]\xf9\xf5]\xe3B\xa6?\xb8\x01<N`T\xb5?'
+p109
+tp110
+bsS'probB_'
+p111
+g13
+(g14
+(I0
+tp112
+g16
+tp113
+Rp114
+(I1
+(I0
+tp115
+g47
+I00
+g60
+tp116
+bsS'cache_size'
+p117
+I200
+sS'gamma'
+p118
+S'auto'
+p119
+sb.
\ No newline at end of file
--- /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
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+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
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+0	51	48	-73	0
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+0	43	61	-49	0
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+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
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+0	51	48	-73	0
+0	58	65	-49	0
+0	43	61	-49	0
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+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
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+2	-63	9	-106	1
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+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
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+3	39	-99	-7	3
+3	48	-115	-5	3
+3	39	-96	2	3
+3	31	-109	9	3
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--- /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 @@
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+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
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
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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
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/train.tabular	Mon May 02 16:15:51 2016 -0400
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/train_set.tabular	Mon May 02 16:15:51 2016 -0400
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/vectorizer_result01.mtx	Mon May 02 16:15:51 2016 -0400
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/vectorizer_result02.mtx	Mon May 02 16:15:51 2016 -0400
@@ -0,0 +1,7346 @@
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/vectorizer_result03.mtx	Mon May 02 16:15:51 2016 -0400
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/vectorizer_result04.mtx	Mon May 02 16:15:51 2016 -0400
@@ -0,0 +1,9697 @@
+%%MatrixMarket matrix coordinate real general
+%
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