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Changeset 3:1c5dcef5ce0f (2024-05-07)

Previous changeset 2:62e3a4e8c54c (2020-01-16) Next changeset 4:f234e2e59d76 (2024-08-07)

Commit message:
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/plotly_ml_performance_plots commit 271a4454eea5902e29da4b8dfa7b9124fefac6bc

modified:
plot_ml_performance.py
plotly_ml_performance_plots.xml
test-data/binary_prediction_sgd.tabular
test-data/prediction_binary_knn.tabular
test-data/prediction_binary_linearsvm.tabular
test-data/prediction_binary_rfc.tabular
test-data/prediction_multi_lr.tabular

added:
test-data/binary_test_label_knn.tabular
test-data/model_binary_knn.h5mlm
test-data/model_binary_linearsvm.h5mlm
test-data/model_binary_rfc.h5mlm
test-data/model_binary_sgd.h5mlm
test-data/model_multi_lr.h5mlm

removed:
test-data/cnf_binary_knn.html
test-data/cnf_binary_linearsvm.html
test-data/cnf_binary_rfc.html
test-data/cnf_binary_sgd.html
test-data/cnf_multi_lr.html
test-data/prf_binary_knn.html
test-data/prf_binary_linearsvm.html
test-data/prf_binary_rfc.html
test-data/prf_binary_sgd.html
test-data/prf_multi_lr.html
test-data/roc_auc_binary_knn.html
test-data/roc_auc_binary_linearsvm.html
test-data/roc_auc_binary_rfc.html
test-data/roc_auc_binary_sgd.html
test-data/roc_auc_multi_lr.html

diff -r 62e3a4e8c54c -r 1c5dcef5ce0f plot_ml_performance.py
--- a/plot_ml_performance.py Thu Jan 16 13:49:49 2020 -0500
+++ b/plot_ml_performance.py Tue May 07 14:11:16 2024 +0000

[

@@ -1,9 +1,12 @@
import argparse
+
import pandas as pd
import plotly
-import pickle
import plotly.graph_objs as go
-from sklearn.metrics import confusion_matrix, precision_recall_fscore_support, roc_curve, auc
+from galaxy_ml.model_persist import load_model_from_h5
+from galaxy_ml.utils import clean_params
+from sklearn.metrics import (auc, confusion_matrix,
+                             precision_recall_fscore_support, roc_curve)
from sklearn.preprocessing import label_binarize

@@ -16,8 +19,8 @@
         infile_trained_model: str, input trained model file (zip)
     """

-    df_input = pd.read_csv(infile_input, sep='\t', parse_dates=True)
-    df_output = pd.read_csv(infile_output, sep='\t', parse_dates=True)
+    df_input = pd.read_csv(infile_input, sep="\t", parse_dates=True)
+    df_output = pd.read_csv(infile_output, sep="\t", parse_dates=True)
     true_labels = df_input.iloc[:, -1].copy()
     predicted_labels = df_output.iloc[:, -1].copy()
     axis_labels = list(set(true_labels))
@@ -27,47 +30,40 @@
             z=c_matrix,
             x=axis_labels,
             y=axis_labels,
-            colorscale='Portland',
+            colorscale="Portland",
         )
     ]

     layout = go.Layout(
-        title='Confusion Matrix between true and predicted class labels',
-        xaxis=dict(title='Predicted class labels'),
-        yaxis=dict(title='True class labels')
+        title="Confusion Matrix between true and predicted class labels",
+        xaxis=dict(title="Predicted class labels"),
+        yaxis=dict(title="True class labels"),
     )

     fig = go.Figure(data=data, layout=layout)
     plotly.offline.plot(fig, filename="output_confusion.html", auto_open=False)

     # plot precision, recall and f_score for each class label
-    precision, recall, f_score, _ = precision_recall_fscore_support(true_labels, predicted_labels)
+    precision, recall, f_score, _ = precision_recall_fscore_support(
+        true_labels, predicted_labels
+    )

     trace_precision = go.Scatter(
-        x=axis_labels,
-        y=precision,
-        mode='lines+markers',
-        name='Precision'
+        x=axis_labels, y=precision, mode="lines+markers", name="Precision"
     )

     trace_recall = go.Scatter(
-        x=axis_labels,
-        y=recall,
-        mode='lines+markers',
-        name='Recall'
+        x=axis_labels, y=recall, mode="lines+markers", name="Recall"
     )

     trace_fscore = go.Scatter(
-        x=axis_labels,
-        y=f_score,
-        mode='lines+markers',
-        name='F-score'
+        x=axis_labels, y=f_score, mode="lines+markers", name="F-score"
     )

     layout_prf = go.Layout(
-        title='Precision, recall and f-score of true and predicted class labels',
-        xaxis=dict(title='Class labels'),
-        yaxis=dict(title='Precision, recall and f-score')
+        title="Precision, recall and f-score of true and predicted class labels",
+        xaxis=dict(title="Class labels"),
+        yaxis=dict(title="Precision, recall and f-score"),
     )

     data_prf = [trace_precision, trace_recall, trace_fscore]
@@ -75,8 +71,8 @@
     plotly.offline.plot(fig_prf, filename="output_prf.html", auto_open=False)

     # plot roc and auc curves for different classes
-    with open(infile_trained_model, 'rb') as model_file:
-        model = pickle.load(model_file)
+    classifier_object = load_model_from_h5(infile_trained_model)
+    model = clean_params(classifier_object)

     # remove the last column (label column)
     test_data = df_input.iloc[:, :-1]
@@ -84,9 +80,9 @@

     try:
         # find the probability estimating method
-        if 'predict_proba' in model_items:
+        if "predict_proba" in model_items:
             y_score = model.predict_proba(test_data)
-        elif 'decision_function' in model_items:
+        elif "decision_function" in model_items:
             y_score = model.decision_function(test_data)

         true_labels_list = true_labels.tolist()
@@ -104,43 +100,44 @@
                 trace = go.Scatter(
                     x=fpr[i],
                     y=tpr[i],
-                    mode='lines+markers',
-                    name='ROC curve of class {0} (AUC = {1:0.2f})'.format(i, roc_auc[i])
+                    mode="lines+markers",
+                    name="ROC curve of class {0} (AUC = {1:0.2f})".format(
+                        i, roc_auc[i]
+                    ),
                 )
                 data_roc.append(trace)
         else:
             try:
                 y_score_binary = y_score[:, 1]
-            except:
+            except Exception:
                 y_score_binary = y_score
             fpr, tpr, _ = roc_curve(one_hot_labels, y_score_binary, pos_label=1)
             roc_auc = auc(fpr, tpr)
             trace = go.Scatter(
                 x=fpr,
                 y=tpr,
-                mode='lines+markers',
-                name='ROC curve (AUC = {0:0.2f})'.format(roc_auc)
+                mode="lines+markers",
+                name="ROC curve (AUC = {0:0.2f})".format(roc_auc),
             )
             data_roc.append(trace)

-        trace_diag = go.Scatter(
-            x=[0, 1],
-            y=[0, 1],
-            mode='lines',
-            name='Chance'
-        )
+        trace_diag = go.Scatter(x=[0, 1], y=[0, 1], mode="lines", name="Chance")
         data_roc.append(trace_diag)
         layout_roc = go.Layout(
-            title='Receiver operating characteristics (ROC) and area under curve (AUC)',
-            xaxis=dict(title='False positive rate'),
-            yaxis=dict(title='True positive rate')
+            title="Receiver operating characteristics (ROC) and area under curve (AUC)",
+            xaxis=dict(title="False positive rate"),
+            yaxis=dict(title="True positive rate"),
         )

         fig_roc = go.Figure(data=data_roc, layout=layout_roc)
         plotly.offline.plot(fig_roc, filename="output_roc.html", auto_open=False)

     except Exception as exp:
-        print("Plotting the ROC-AUC graph failed. This exception was raised: {}".format(exp))
+        print(
+            "Plotting the ROC-AUC graph failed. This exception was raised: {}".format(
+                exp
+            )
+        )

if __name__ == "__main__":

diff -r 62e3a4e8c54c -r 1c5dcef5ce0f plotly_ml_performance_plots.xml
--- a/plotly_ml_performance_plots.xml Thu Jan 16 13:49:49 2020 -0500
+++ b/plotly_ml_performance_plots.xml Tue May 07 14:11:16 2024 +0000

[

b'@@ -1,10 +1,7 @@\n-<tool id="plotly_ml_performance_plots" name="Plot confusion matrix, precision, recall and ROC and AUC curves" version="0.2">\n+<tool id="plotly_ml_performance_plots" name="Plot confusion matrix, precision, recall and ROC and AUC curves" version="0.3" profile="22.05">\n <description>of tabular data</description>\n <requirements>\n- <requirement type="package" version="0.25.3">pandas</requirement>\n- <requirement type="package" version="4.3.0">plotly</requirement>\n- <requirement type="package" version="0.21.3">scikit-learn</requirement>\n- <requirement type="package" version="1.4.1">scipy</requirement>\n+\t<requirement type="package" version="0.10.0">galaxy-ml</requirement>\n </requirements>\n <version_command>echo $version</version_command>\n <command detect_errors="aggressive"><![CDATA[\n@@ -17,7 +14,7 @@\n <inputs>\n <param name="infile_input" type="data" format="tabular" label="Select input data file :" help="Input data is a matrix (tabular) where each column is a feature and the last column contains the (true or original) class labels."/>\n <param name="infile_output" type="data" format="tabular" label="Select predicted data file :" help="Predicted data is a matrix (tabular) where each column is a feature and the last column contains the predicted class labels."/>\n- <param name="infile_trained_model" type="data" format="zip" label="Select trained model :" help="This file is a final model trained on training data."/>\n+ <param name="infile_trained_model" type="data" format="h5mlm" label="Select trained model :" help="This file is a final model trained on training data."/>\n </inputs>\n \n <outputs>\n@@ -30,48 +27,112 @@\n <test>\n <param name="infile_input" value="binary_test_label.tabular" ftype="tabular"/>\n <param name="infile_output" value="binary_prediction_sgd.tabular" ftype="tabular"/>\n- <param name="infile_trained_model" value="model_binary_sgd.zip" ftype="zip"/>\n- <output name="output_confusion" file="cnf_binary_sgd.html" compare="sim_size"/>\n- <output name="output_prf" file="prf_binary_sgd.html" compare="sim_size"/>\n- <output name="output_roc" file="roc_auc_binary_sgd.html" compare="sim_size"/>\n+ <param name="infile_trained_model" value="model_binary_sgd.h5mlm" ftype="h5mlm"/>\n+\t <output name="output_confusion">\n+ <assert_contents>\n+\t\t <has_size value="3486809" delta="10000" />\n+\t\t <has_text text="html" />\n+\t\t</assert_contents>\n+ </output>\n+\t <output name="output_prf">\n+\t\t<assert_contents>\n+\t\t <has_size value="3486974" delta="10000" />\n+\t\t <has_text text="html" />\n+\t\t</assert_contents>\n+\t </output>\n </test>\n- \n <test>\n <param name="infile_input" value="binary_test_label.tabular" ftype="tabular"/>\n <param name="infile_output" value="prediction_binary_linearsvm.tabular" ftype="tabular"/>\n- <param name="infile_trained_model" value="model_binary_linearsvm.zip" ftype="zip"/>\n- <output name="output_confusion" file="cnf_binary_linearsvm.html" compare="sim_size"/>\n- <output name="output_prf" file="prf_binary_linearsvm.html" compare="sim_size"/>\n- <output name="output_roc" file="roc_auc_binary_linearsvm.html" compare="sim_size"/>\n+ <param name="infile_trained_model" value="model_binary_linearsvm.h5mlm" ftype="h5mlm"/>\n+\t <output name="output_confusion">\n+\t <assert_contents>\n+\t\t <has_size value="3486810" delta="10000" />\n+\t\t <has_text text="html" />\n+ </assert_contents>\n+\t </output>\n+ <output name="output_prf">\n+\t\t<assert_contents>\n+\t\t <has_size value="3486973" delta="10000" />\n+\t\t <has_text text="html" />\n+\t </assert_contents>\n+\t </output>\n+\t <output name="output_roc">\n+\t\t<assert_contents>\n+ <has_size value="3497518" delta="10'..b'lue="prediction_binary_rfc.tabular" ftype="tabular"/>\n- <param name="infile_trained_model" value="model_binary_rfc.zip" ftype="zip"/>\n- <output name="output_confusion" file="cnf_binary_rfc.html" compare="sim_size"/>\n- <output name="output_prf" file="prf_binary_rfc.html" compare="sim_size"/>\n- <output name="output_roc" file="roc_auc_binary_rfc.html" compare="sim_size"/>\n+ <param name="infile_trained_model" value="model_binary_rfc.h5mlm" ftype="h5mlm"/>\n+ <output name="output_confusion">\n+\t <assert_contents>\n+\t\t <has_size value="3486806" delta="10000" />\n+\t\t <has_text text="html" />\n+ </assert_contents>\n+\t </output>\n+ <output name="output_prf">\n+\t <assert_contents>\n+\t\t <has_size value="3486883" delta="10000" />\n+\t\t <has_text text="html" />\n+\t </assert_contents>\n+\t </output>\n+\t <output name="output_roc">\n+\t\t<assert_contents>\n+ <has_size value="3488335" delta="10000" />\n+\t\t <has_text text="html" />\n+\t </assert_contents>\n+\t </output>\n </test>\n- \n <test>\n- <param name="infile_input" value="binary_test_label.tabular" ftype="tabular"/>\n+ <param name="infile_input" value="binary_test_label_knn.tabular" ftype="tabular"/>\n <param name="infile_output" value="prediction_binary_knn.tabular" ftype="tabular"/>\n- <param name="infile_trained_model" value="model_binary_knn.zip" ftype="zip"/>\n- <output name="output_confusion" file="cnf_binary_knn.html" compare="sim_size"/>\n- <output name="output_prf" file="prf_binary_knn.html" compare="sim_size"/>\n- <output name="output_roc" file="roc_auc_binary_knn.html" compare="sim_size"/>\n+ <param name="infile_trained_model" value="model_binary_knn.h5mlm" ftype="h5mlm"/>\n+ <output name="output_confusion">\n+\t <assert_contents>\n+\t\t <has_size value="3486856" delta="10000" />\n+\t\t <has_text text="html" />\n+ </assert_contents>\n+\t </output>\n+ <output name="output_prf">\n+\t <assert_contents>\n+\t\t <has_size value="3486928" delta="10000" />\n+\t\t <has_text text="html" />\n+\t </assert_contents>\n+\t </output>\n+\t <output name="output_roc">\n+\t\t<assert_contents>\n+ <has_size value="3487215" delta="10000" />\n+\t\t <has_text text="html" />\n+\t\t</assert_contents>\n+\t </output>\n </test>\n- \n <test>\n <param name="infile_input" value="multi_test_label.tabular" ftype="tabular"/>\n <param name="infile_output" value="prediction_multi_lr.tabular" ftype="tabular"/>\n- <param name="infile_trained_model" value="model_multi_lr.zip" ftype="zip"/>\n- <output name="output_confusion" file="cnf_multi_lr.html" compare="sim_size"/>\n- <output name="output_prf" file="prf_multi_lr.html" compare="sim_size"/>\n- <output name="output_roc" file="roc_auc_multi_lr.html" compare="sim_size"/>\n- </test>\n- \n+ <param name="infile_trained_model" value="model_multi_lr.h5mlm" ftype="h5mlm"/>\n+ <output name="output_confusion">\n+\t <assert_contents>\n+\t\t <has_size value="3486832" delta="10000" />\n+\t\t <has_text text="html" />\n+ </assert_contents>\n+\t </output>\n+ <output name="output_prf">\n+\t\t<assert_contents>\n+\t\t <has_size value="3487035" delta="10000" />\n+\t\t <has_text text="html" />\n+\t </assert_contents>\n+\t </output>\n+\t <output name="output_roc">\n+\t <assert_contents>\n+ <has_size value="3493184" delta="10000" />\n+\t\t <has_text text="html" />\n+\t\t</assert_contents>\n+\t </output>\n+\t</test>\n </tests>\n <help><![CDATA[\n **What it does**\n@@ -83,4 +144,7 @@\n \n ]]>\n </help>\n+ <citations>\n+ <citation type="doi">10.1371/journal.pcbi.1009014</citation>\n+ </citations>\n </tool>\n'

diff -r 62e3a4e8c54c -r 1c5dcef5ce0f test-data/binary_prediction_sgd.tabular
--- a/test-data/binary_prediction_sgd.tabular Thu Jan 16 13:49:49 2020 -0500
+++ b/test-data/binary_prediction_sgd.tabular Tue May 07 14:11:16 2024 +0000

b'@@ -1,801 +1,801 @@\n--0.7440000000000001\t-1.39\t1\n--0.47200000000000003\t0.267\t1\n-0.304\t1.61\t1\n+-0.744\t-1.39\t1\n+-0.472\t0.267\t1\n+0.304\t1.61\t-1\n -0.0439\t0.305\t1\n--1.96\t-1.09\t-1\n+-1.96\t-1.09\t1\n 1.31\t0.17\t1\n--1.78\t-0.253\t-1\n--1.21\t0.9179999999999999\t-1\n+-1.78\t-0.253\t1\n+-1.21\t0.918\t1\n 0.457\t0.191\t1\n 0.998\t0.37\t1\n-0.513\t1.5\t1\n--0.7140000000000001\t-0.161\t1\n-0.0722\t1.8\t1\n+0.513\t1.5\t-1\n+-0.714\t-0.161\t1\n+0.0722\t1.8\t-1\n 1.33\t-0.0673\t1\n 0.508\t-0.331\t1\n 0.862\t-1.24\t1\n-0.65\t1.86\t1\n-1.74\t-0.14300000000000002\t1\n-0.41700000000000004\t-1.54\t1\n+0.65\t1.86\t-1\n+1.74\t-0.143\t1\n+0.417\t-1.54\t1\n 0.466\t0.281\t1\n-1.73\t0.9790000000000001\t1\n+1.73\t0.979\t-1\n -0.314\t-0.72\t1\n 0.0981\t0.465\t1\n--1.08\t1.01\t-1\n-2.37\t1.07\t1\n-0.14300000000000002\t-0.7859999999999999\t1\n+-1.08\t1.01\t1\n+2.37\t1.07\t-1\n+0.143\t-0.786\t1\n 0.032\t-1.5\t1\n-0.7390000000000001\t2.14\t1\n-0.396\t1.81\t1\n-0.5379999999999999\t1.38\t1\n+0.739\t2.14\t-1\n+0.396\t1.81\t-1\n+0.538\t1.38\t-1\n 0.0325\t-1.46\t1\n--0.391\t1.32\t1\n--0.695\t1.08\t-1\n--1.84\t-0.846\t-1\n--0.8240000000000001\t1.1\t-1\n+-0.391\t1.32\t-1\n+-0.695\t1.08\t1\n+-1.84\t-0.846\t1\n+-0.824\t1.1\t1\n 1.16\t-1.24\t1\n-0.7\t1.14\t1\n--0.17\t1.18\t1\n--0.0932\t0.47200000000000003\t1\n-0.16399999999999998\t-1.18\t1\n-0.44299999999999995\t1.54\t1\n--1.22\t0.0836\t-1\n+0.7\t1.14\t-1\n+-0.17\t1.18\t-1\n+-0.0932\t0.472\t1\n+0.164\t-1.18\t1\n+0.443\t1.54\t-1\n+-1.22\t0.0836\t1\n -0.188\t-1.27\t1\n 0.109\t-0.522\t1\n-1.62\t1.19\t1\n--0.853\t0.358\t-1\n--1.69\t-1.14\t-1\n+1.62\t1.19\t-1\n+-0.853\t0.358\t1\n+-1.69\t-1.14\t1\n 0.725\t-0.99\t1\n 0.25\t-1.1\t1\n--1.22\t0.569\t-1\n+-1.22\t0.569\t1\n 0.627\t0.125\t1\n -0.0699\t-1.2\t1\n-0.594\t1.8\t1\n--0.9009999999999999\t-1.56\t-1\n+0.594\t1.8\t-1\n+-0.901\t-1.56\t1\n 1.02\t0.0975\t1\n -0.149\t-0.0185\t1\n -0.226\t-1.09\t1\n-1.11\t0.685\t1\n--0.301\t1.69\t1\n-0.47100000000000003\t-0.445\t1\n--0.8270000000000001\t1.23\t-1\n+1.11\t0.685\t-1\n+-0.301\t1.69\t-1\n+0.471\t-0.445\t1\n+-0.827\t1.23\t1\n -0.672\t-0.0414\t1\n 0.606\t-0.877\t1\n -0.64\t0.705\t1\n 0.14\t-0.8\t1\n 0.425\t-1.21\t1\n-0.966\t-0.19899999999999998\t1\n-1.06\t0.629\t1\n-0.8390000000000001\t-1.15\t1\n-0.379\t1.74\t1\n+0.966\t-0.199\t1\n+1.06\t0.629\t-1\n+0.839\t-1.15\t1\n+0.379\t1.74\t-1\n 0.603\t-1.0\t1\n--0.46299999999999997\t-1.2\t1\n-1.18\t1.42\t1\n+-0.463\t-1.2\t1\n+1.18\t1.42\t-1\n 1.09\t-1.12\t1\n 0.9\t-1.36\t1\n 1.11\t-1.1\t1\n 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diff -r 62e3a4e8c54c -r 1c5dcef5ce0f test-data/binary_test_label_knn.tabular
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
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diff -r 62e3a4e8c54c -r 1c5dcef5ce0f test-data/cnf_binary_knn.html
--- a/test-data/cnf_binary_knn.html Thu Jan 16 13:49:49 2020 -0500
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diff -r 62e3a4e8c54c -r 1c5dcef5ce0f test-data/cnf_binary_sgd.html
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diff -r 62e3a4e8c54c -r 1c5dcef5ce0f test-data/prediction_binary_linearsvm.tabular
--- a/test-data/prediction_binary_linearsvm.tabular Thu Jan 16 13:49:49 2020 -0500
+++ b/test-data/prediction_binary_linearsvm.tabular Tue May 07 14:11:16 2024 +0000

b'@@ -1,433 +1,433 @@\n--0.744\t-1.39\t0\n--0.47200000000000003\t0.267\t-1\n+-0.744\t-1.39\t1\n+-0.472\t0.267\t-1\n 0.304\t1.61\t-1\n -0.0439\t0.305\t-1\n -1.96\t-1.09\t1\n 1.31\t0.17\t-1\n--1.78\t-0.253\t-1\n--1.21\t0.9179999999999999\t-1\n+-1.78\t-0.253\t1\n+-1.21\t0.918\t-1\n 0.457\t0.191\t-1\n 0.998\t0.37\t-1\n 0.513\t1.5\t-1\n--0.7140000000000001\t-0.161\t-1\n+-0.714\t-0.161\t1\n 0.0722\t1.8\t-1\n 1.33\t-0.0673\t-1\n 0.508\t-0.331\t-1\n-0.862\t-1.24\t-1\n+0.862\t-1.24\t1\n 0.65\t1.86\t-1\n-1.74\t-0.14300000000000002\t-1\n-0.41700000000000004\t-1.54\t-1\n+1.74\t-0.143\t-1\n+0.417\t-1.54\t1\n 0.466\t0.281\t-1\n-1.73\t0.9790000000000001\t-1\n--0.314\t-0.72\t-1\n+1.73\t0.979\t-1\n+-0.314\t-0.72\t1\n 0.0981\t0.465\t-1\n -1.08\t1.01\t-1\n 2.37\t1.07\t-1\n-0.14300000000000002\t-0.7859999999999999\t-1\n-0.032\t-1.5\t-1\n-0.7390000000000001\t2.14\t-1\n+0.143\t-0.786\t1\n+0.032\t-1.5\t1\n+0.739\t2.14\t-1\n 0.396\t1.81\t-1\n-0.5379999999999999\t1.38\t-1\n-0.0325\t-1.46\t-1\n+0.538\t1.38\t-1\n+0.0325\t-1.46\t1\n -0.391\t1.32\t-1\n -0.695\t1.08\t-1\n--1.84\t-0.846\t-1\n--0.8240000000000001\t1.1\t-1\n-1.16\t-1.24\t-1\n+-1.84\t-0.846\t1\n+-0.824\t1.1\t-1\n+1.16\t-1.24\t1\n 0.7\t1.14\t-1\n -0.17\t1.18\t-1\n--0.0932\t0.47200000000000003\t-1\n-0.16399999999999998\t-1.18\t-1\n-0.44299999999999995\t1.54\t-1\n--1.22\t0.0836\t-1\n--0.188\t-1.27\t-1\n-0.109\t-0.522\t-1\n+-0.0932\t0.472\t-1\n+0.164\t-1.18\t1\n+0.443\t1.54\t-1\n+-1.22\t0.0836\t1\n+-0.188\t-1.27\t1\n+0.109\t-0.522\t1\n 1.62\t1.19\t-1\n--0.853\t0.358\t-1\n--1.69\t-1.14\t-1\n-0.725\t-0.99\t-1\n-0.25\t-1.1\t-1\n--1.22\t0.569\t-1\n+-0.853\t0.358\t1\n+-1.69\t-1.14\t1\n+0.725\t-0.99\t1\n+0.25\t-1.1\t1\n+-1.22\t0.569\t1\n 0.627\t0.125\t-1\n--0.0699\t-1.2\t-1\n+-0.0699\t-1.2\t1\n 0.594\t1.8\t-1\n--0.9009999999999999\t-1.56\t-1\n+-0.901\t-1.56\t1\n 1.02\t0.0975\t-1\n -0.149\t-0.0185\t-1\n--0.226\t-1.09\t-1\n+-0.226\t-1.09\t1\n 1.11\t0.685\t-1\n -0.301\t1.69\t-1\n-0.47100000000000003\t-0.445\t-1\n--0.8270000000000001\t1.23\t-1\n--0.672\t-0.0414\t-1\n-0.606\t-0.877\t-1\n+0.471\t-0.445\t1\n+-0.827\t1.23\t-1\n+-0.672\t-0.0414\t1\n+0.606\t-0.877\t1\n -0.64\t0.705\t-1\n-0.14\t-0.8\t-1\n-0.425\t-1.21\t-1\n-0.966\t-0.19899999999999998\t-1\n+0.14\t-0.8\t1\n+0.425\t-1.21\t1\n+0.966\t-0.199\t-1\n 1.06\t0.629\t-1\n-0.8390000000000001\t-1.15\t-1\n+0.839\t-1.15\t1\n 0.379\t1.74\t-1\n-0.603\t-1.0\t-1\n--0.46299999999999997\t-1.2\t-1\n+0.603\t-1.0\t1\n+-0.463\t-1.2\t1\n 1.18\t1.42\t-1\n-1.09\t-1.12\t-1\n-0.9\t-1.36\t-1\n-1.11\t-1.1\t-1\n+1.09\t-1.12\t1\n+0.9\t-1.36\t1\n+1.11\t-1.1\t1\n 1.46\t-0.111\t-1\n-0.242\t0.34700000000000003\t-1\n+0.242\t0.347\t-1\n 0.669\t0.98\t-1\n--1.2\t-0.826\t-1\n--1.13\t0.9279999999999999\t-1\n+-1.2\t-0.826\t1\n+-1.13\t0.928\t-1\n -0.799\t1.11\t-1\n--0.10800000000000001\t1.7\t-1\n--1.18\t0.6920000000000001\t-1\n--0.787\t-0.113\t-1\n--0.41200000000000003\t-0.6890000000000001\t-1\n+-0.108\t1.7\t-1\n+-1.18\t0.692\t-1\n+-0.787\t-0.113\t1\n+-0.412\t-0.689\t1\n -0.452\t0.524\t-1\n-0.29\t-0.515\t-1\n--0.518\t-0.914\t-1\n--1.1\t0.419\t-1\n+0.29\t-0.515\t1\n+-0.518\t-0.914\t1\n+-1.1\t0.419\t1\n 1.34\t1.44\t-1\n--1.46\t0.594\t-1\n+-1.46\t0.594\t1\n -0.613\t1.1\t-1\n 1.5\t0.0442\t-1\n 1.34\t-0.0272\t-1\n--0.146\t-0.8690000000000001\t-1\n-0.0726\t-1.31\t-1\n--0.198\t-0.6609999999999999\t-1\n--0.0776\t-1.35\t-1\n--1.22\t-0.68\t-1\n-1.17\t0.40700000000000003\t-1\n+-0.146\t-0.869\t1\n+0.0726\t-1.31\t1\n+-0.198\t-0.661\t1\n+-0.0776\t-1.35\t1\n+-1.22\t-0.68\t1\n+1.17\t0.407\t-1\n 1.34\t0.0998\t-1\n-1.25\t-1.25\t-1\n-0.7120000000000001\t1.49\t-1\n--0.516\t-0.915\t-1\n--1.63\t0.728\t-1\n--0.514\t-1.21\t-1\n-1.12\t0.8220000000000001\t-1\n--0.076\t-1.12\t-1\n--0.6779999999999999\t-0.41700000000000004\t-1\n--0.897\t-1.04\t-1\n+1.25\t-1.25\t1\n+0.712\t1.49\t-1\n+-0.516\t-0.915\t1\n+-1.63\t0.728\t1\n+-0.514\t-1.21\t1\n+1.12\t0.822\t-1\n+-0.076\t-1.12\t1\n+-0.678\t-0.417\t1\n+-0.897\t-1.04\t1\n 1.12\t0.375\t-1\n -1.94\t-1.61\t1\n--0.7559999999999999\t-0.679\t-1\n-0.825\t-1.28\t-1\n+-0.756\t-0.679\t1\n+0.825\t-1.28\t1\n 1.8\t0.0607\t-1\n-0.10800000000000001\t-1.21\t-1\n+0.108\t-1.21\t1\n 2.18\t1.21\t-1\n 0.634\t0.366\t-1\n 1.26\t0.799\t-1\n--0.7020000000000001\t-0.8109999999999999\t-1\n--0.336\t-0.0523\t-1\n--0.7290000000000001\t1.5\t-1\n-1.3\t0.7490000000000001\t-1\n-0.28300000000000003\t0.39399999999999996\t-1\n+-0.702\t-0.811\t1\n+-0.336\t-0.0523\t1\n+-0.729\t1.5\t-1\n+1.3\t0.749\t-1\n+0.283\t0.394\t-1\n 0.247\t1.65\t-1\n 0.212\t1.81\t-1\n 1.08\t-0.628\t-1\n--0.852\t-0.298\t-1\n--1.77\t-0.5920000000000001\t-1\n+-0.852\t-0.298\t1\n+-1.77\t-0.592\t1\n -0.251\t0.327\t-1\n-0.41700000000000004\t-1.28\t-1\n--0.12\t-1.22\t-1\n+0.417\t-1.2'..b'.23399999999999999\t-0.8220000000000001\t-1\n--1.84\t-0.865\t-1\n+-0.234\t-0.656\t1\n+-1.45\t-1.29\t1\n+0.234\t-0.822\t1\n+-1.84\t-0.865\t1\n -1.63\t-1.32\t1\n--0.715\t-0.9690000000000001\t-1\n-0.0973\t-1.33\t-1\n--0.551\t0.28800000000000003\t-1\n-1.39\t-0.013000000000000001\t-1\n-0.215\t-1.66\t-1\n+-0.715\t-0.969\t1\n+0.0973\t-1.33\t1\n+-0.551\t0.288\t-1\n+1.39\t-0.013\t-1\n+0.215\t-1.66\t1\n 0.0224\t1.43\t-1\n--0.33799999999999997\t-1.33\t-1\n--0.693\t-0.113\t-1\n-0.0533\t-1.02\t-1\n--0.153\t-1.22\t-1\n--1.18\t0.0302\t-1\n-1.15\t0.32899999999999996\t-1\n-1.31\t-1.4\t-1\n+-0.338\t-1.33\t1\n+-0.693\t-0.113\t1\n+0.0533\t-1.02\t1\n+-0.153\t-1.22\t1\n+-1.18\t0.0302\t1\n+1.15\t0.329\t-1\n+1.31\t-1.4\t1\n -0.285\t1.98\t-1\n 1.06\t-0.0553\t-1\n--0.904\t-0.203\t-1\n-0.6609999999999999\t-0.19899999999999998\t-1\n-0.8959999999999999\t-1.27\t-1\n--1.54\t-0.618\t-1\n+-0.904\t-0.203\t1\n+0.661\t-0.199\t-1\n+0.896\t-1.27\t1\n+-1.54\t-0.618\t1\n 1.29\t-0.657\t-1\n -1.67\t-1.5\t1\n--1.36\t-0.848\t-1\n+-1.36\t-0.848\t1\n 1.98\t-0.0252\t-1\n 0.485\t0.635\t-1\n--0.674\t0.8420000000000001\t-1\n-0.722\t-0.975\t-1\n+-0.674\t0.842\t-1\n+0.722\t-0.975\t1\n 1.02\t-0.625\t-1\n-1.26\t-0.18100000000000002\t-1\n--0.6579999999999999\t-1.31\t-1\n--0.405\t-1.25\t-1\n+1.26\t-0.181\t-1\n+-0.658\t-1.31\t1\n+-0.405\t-1.25\t1\n 1.27\t0.493\t-1\n-0.9329999999999999\t-0.27699999999999997\t-1\n--0.815\t-0.682\t-1\n--1.51\t-0.769\t-1\n-0.11699999999999999\t-1.07\t-1\n+0.933\t-0.277\t-1\n+-0.815\t-0.682\t1\n+-1.51\t-0.769\t1\n+0.117\t-1.07\t1\n 0.384\t2.15\t-1\n -1.32\t1.1\t-1\n-1.2\t-1.65\t-1\n+1.2\t-1.65\t1\n 0.0529\t1.52\t-1\n 1.46\t0.0373\t-1\n--0.607\t-1.6\t-1\n--1.06\t-0.5489999999999999\t-1\n+-0.607\t-1.6\t1\n+-1.06\t-0.549\t1\n -1.39\t0.862\t-1\n 0.527\t0.51\t-1\n 1.15\t-0.451\t-1\n -0.171\t0.0105\t-1\n--1.63\t0.524\t-1\n+-1.63\t0.524\t1\n 2.2\t-0.665\t-1\n 0.826\t1.42\t-1\n -0.138\t-0.0524\t-1\n@@ -724,78 +724,78 @@\n 0.877\t0.161\t-1\n 1.17\t0.446\t-1\n 0.647\t0.317\t-1\n--1.73\t-0.242\t-1\n-0.631\t-0.674\t-1\n--0.973\t-0.047\t-1\n--0.4\t0.00463\t-1\n--1.14\t-1.27\t-1\n+-1.73\t-0.242\t1\n+0.631\t-0.674\t1\n+-0.973\t-0.047\t1\n+-0.4\t0.00463\t1\n+-1.14\t-1.27\t1\n 0.42\t1.1\t-1\n-0.43\t-0.654\t-1\n+0.43\t-0.654\t1\n 1.49\t0.365\t-1\n -0.643\t1.68\t-1\n-0.698\t-0.655\t-1\n+0.698\t-0.655\t1\n -0.222\t2.47\t-1\n--1.22\t-0.0961\t-1\n+-1.22\t-0.0961\t1\n -0.276\t1.05\t-1\n--0.253\t-0.406\t-1\n--1.38\t0.6779999999999999\t-1\n--1.13\t-0.44299999999999995\t-1\n+-0.253\t-0.406\t1\n+-1.38\t0.678\t1\n+-1.13\t-0.443\t1\n 1.3\t0.175\t-1\n 1.64\t1.46\t-1\n 1.48\t1.78\t-1\n--1.61\t-0.363\t-1\n--1.52\t-1.23\t-1\n--0.0657\t-1.19\t-1\n+-1.61\t-0.363\t1\n+-1.52\t-1.23\t1\n+-0.0657\t-1.19\t1\n -0.653\t0.433\t-1\n 2.48\t1.21\t-1\n--0.9590000000000001\t1.08\t-1\n-0.8420000000000001\t-0.37200000000000005\t-1\n--0.402\t-1.11\t-1\n--0.29100000000000004\t0.561\t-1\n--1.02\t-0.22399999999999998\t-1\n-0.45\t-0.10400000000000001\t-1\n--1.88\t-0.45399999999999996\t-1\n--0.5820000000000001\t-0.752\t-1\n+-0.959\t1.08\t-1\n+0.842\t-0.372\t-1\n+-0.402\t-1.11\t1\n+-0.291\t0.561\t-1\n+-1.02\t-0.224\t1\n+0.45\t-0.104\t-1\n+-1.88\t-0.454\t1\n+-0.582\t-0.752\t1\n -0.594\t1.24\t-1\n--1.49\t-0.00325\t-1\n+-1.49\t-0.00325\t1\n 0.552\t1.04\t-1\n-1.06\t0.44299999999999995\t-1\n-0.406\t-0.7070000000000001\t-1\n+1.06\t0.443\t-1\n+0.406\t-0.707\t1\n 1.15\t0.0436\t-1\n 0.612\t1.37\t-1\n 1.1\t0.508\t-1\n 1.1\t0.604\t-1\n -0.753\t1.18\t-1\n--1.13\t0.41100000000000003\t-1\n--0.872\t0.26\t-1\n+-1.13\t0.411\t1\n+-0.872\t0.26\t1\n -0.415\t0.256\t-1\n-0.8009999999999999\t-0.639\t-1\n+0.801\t-0.639\t1\n 0.762\t0.125\t-1\n-0.0343\t-1.18\t-1\n+0.0343\t-1.18\t1\n 0.524\t-0.231\t-1\n--0.0262\t-1.18\t-1\n--1.47\t-0.0358\t-1\n+-0.0262\t-1.18\t1\n+-1.47\t-0.0358\t1\n 1.29\t0.152\t-1\n--0.851\t0.18899999999999997\t-1\n+-0.851\t0.189\t1\n -0.961\t1.0\t-1\n--0.7759999999999999\t0.127\t-1\n--0.674\t-0.62\t-1\n-0.244\t-0.69\t-1\n--0.9740000000000001\t0.511\t-1\n+-0.776\t0.127\t1\n+-0.674\t-0.62\t1\n+0.244\t-0.69\t1\n+-0.974\t0.511\t-1\n 0.37\t1.03\t-1\n--1.98\t-0.88\t-1\n-0.308\t0.11699999999999999\t-1\n--1.62\t0.46799999999999997\t-1\n--0.843\t-1.08\t-1\n+-1.98\t-0.88\t1\n+0.308\t0.117\t-1\n+-1.62\t0.468\t1\n+-0.843\t-1.08\t1\n 1.0\t1.17\t-1\n--0.9540000000000001\t0.687\t-1\n-0.768\t-0.966\t-1\n+-0.954\t0.687\t-1\n+0.768\t-0.966\t1\n 1.64\t1.12\t-1\n--1.7\t-0.5539999999999999\t-1\n-0.40399999999999997\t0.00999\t-1\n-0.7040000000000001\t-0.9059999999999999\t-1\n+-1.7\t-0.554\t1\n+0.404\t0.00999\t-1\n+0.704\t-0.906\t1\n 0.335\t1.39\t-1\n--1.7\t-0.569\t-1\n+-1.7\t-0.569\t1\n 2.64\t1.14\t-1\n 0.769\t0.772\t-1\n--0.255\t-0.142\t-1\n+-0.255\t-0.142\t1\n'

diff -r 62e3a4e8c54c -r 1c5dcef5ce0f test-data/prediction_binary_rfc.tabular
--- a/test-data/prediction_binary_rfc.tabular Thu Jan 16 13:49:49 2020 -0500
+++ b/test-data/prediction_binary_rfc.tabular Tue May 07 14:11:16 2024 +0000

b'@@ -1,44 +1,44 @@\n--0.744\t-1.39\tpredicted\n--0.47200000000000003\t0.267\t1\n-0.304\t1.61\t1\n+-0.744\t-1.39\t-1\n+-0.472\t0.267\t1\n+0.304\t1.61\t-1\n -0.0439\t0.305\t1\n -1.96\t-1.09\t1\n 1.31\t0.17\t-1\n -1.78\t-0.253\t1\n--1.21\t0.9179999999999999\t-1\n+-1.21\t0.918\t-1\n 0.457\t0.191\t1\n 0.998\t0.37\t-1\n 0.513\t1.5\t-1\n--0.7140000000000001\t-0.161\t1\n+-0.714\t-0.161\t1\n 0.0722\t1.8\t-1\n 1.33\t-0.0673\t-1\n 0.508\t-0.331\t1\n 0.862\t-1.24\t1\n-0.65\t1.86\t1\n-1.74\t-0.14300000000000002\t-1\n-0.41700000000000004\t-1.54\t-1\n+0.65\t1.86\t-1\n+1.74\t-0.143\t-1\n+0.417\t-1.54\t-1\n 0.466\t0.281\t1\n-1.73\t0.9790000000000001\t1\n--0.314\t-0.72\t1\n+1.73\t0.979\t1\n+-0.314\t-0.72\t-1\n 0.0981\t0.465\t1\n -1.08\t1.01\t-1\n 2.37\t1.07\t1\n-0.14300000000000002\t-0.7859999999999999\t-1\n+0.143\t-0.786\t-1\n 0.032\t-1.5\t-1\n-0.7390000000000001\t2.14\t-1\n-0.396\t1.81\t-1\n-0.5379999999999999\t1.38\t-1\n+0.739\t2.14\t-1\n+0.396\t1.81\t1\n+0.538\t1.38\t-1\n 0.0325\t-1.46\t-1\n -0.391\t1.32\t-1\n -0.695\t1.08\t-1\n -1.84\t-0.846\t1\n--0.8240000000000001\t1.1\t-1\n+-0.824\t1.1\t-1\n 1.16\t-1.24\t1\n 0.7\t1.14\t-1\n -0.17\t1.18\t-1\n--0.0932\t0.47200000000000003\t1\n-0.16399999999999998\t-1.18\t-1\n-0.44299999999999995\t1.54\t-1\n+-0.0932\t0.472\t1\n+0.164\t-1.18\t-1\n+0.443\t1.54\t-1\n -1.22\t0.0836\t1\n -0.188\t-1.27\t-1\n 0.109\t-0.522\t1\n@@ -47,43 +47,43 @@\n -1.69\t-1.14\t1\n 0.725\t-0.99\t1\n 0.25\t-1.1\t-1\n--1.22\t0.569\t-1\n+-1.22\t0.569\t1\n 0.627\t0.125\t-1\n -0.0699\t-1.2\t-1\n-0.594\t1.8\t1\n--0.9009999999999999\t-1.56\t-1\n+0.594\t1.8\t-1\n+-0.901\t-1.56\t-1\n 1.02\t0.0975\t-1\n -0.149\t-0.0185\t1\n -0.226\t-1.09\t-1\n 1.11\t0.685\t-1\n -0.301\t1.69\t-1\n-0.47100000000000003\t-0.445\t1\n--0.8270000000000001\t1.23\t-1\n+0.471\t-0.445\t1\n+-0.827\t1.23\t-1\n -0.672\t-0.0414\t1\n-0.606\t-0.877\t1\n+0.606\t-0.877\t-1\n -0.64\t0.705\t1\n 0.14\t-0.8\t-1\n 0.425\t-1.21\t-1\n-0.966\t-0.19899999999999998\t1\n+0.966\t-0.199\t1\n 1.06\t0.629\t-1\n-0.8390000000000001\t-1.15\t1\n+0.839\t-1.15\t1\n 0.379\t1.74\t-1\n-0.603\t-1.0\t1\n--0.46299999999999997\t-1.2\t-1\n+0.603\t-1.0\t-1\n+-0.463\t-1.2\t-1\n 1.18\t1.42\t1\n 1.09\t-1.12\t1\n 0.9\t-1.36\t1\n 1.11\t-1.1\t1\n 1.46\t-0.111\t-1\n-0.242\t0.34700000000000003\t1\n+0.242\t0.347\t1\n 0.669\t0.98\t-1\n -1.2\t-0.826\t1\n--1.13\t0.9279999999999999\t-1\n+-1.13\t0.928\t-1\n -0.799\t1.11\t-1\n--0.10800000000000001\t1.7\t1\n--1.18\t0.6920000000000001\t-1\n+-0.108\t1.7\t-1\n+-1.18\t0.692\t-1\n -0.787\t-0.113\t1\n--0.41200000000000003\t-0.6890000000000001\t1\n+-0.412\t-0.689\t-1\n -0.452\t0.524\t1\n 0.29\t-0.515\t1\n -0.518\t-0.914\t-1\n@@ -93,121 +93,121 @@\n -0.613\t1.1\t-1\n 1.5\t0.0442\t-1\n 1.34\t-0.0272\t-1\n--0.146\t-0.8690000000000001\t-1\n+-0.146\t-0.869\t-1\n 0.0726\t-1.31\t-1\n--0.198\t-0.6609999999999999\t1\n+-0.198\t-0.661\t1\n -0.0776\t-1.35\t-1\n -1.22\t-0.68\t1\n-1.17\t0.40700000000000003\t-1\n+1.17\t0.407\t-1\n 1.34\t0.0998\t-1\n 1.25\t-1.25\t1\n-0.7120000000000001\t1.49\t1\n+0.712\t1.49\t1\n -0.516\t-0.915\t-1\n -1.63\t0.728\t-1\n -0.514\t-1.21\t-1\n-1.12\t0.8220000000000001\t-1\n+1.12\t0.822\t-1\n -0.076\t-1.12\t-1\n--0.6779999999999999\t-0.41700000000000004\t1\n+-0.678\t-0.417\t1\n -0.897\t-1.04\t-1\n 1.12\t0.375\t-1\n -1.94\t-1.61\t1\n--0.7559999999999999\t-0.679\t1\n+-0.756\t-0.679\t-1\n 0.825\t-1.28\t1\n 1.8\t0.0607\t-1\n-0.10800000000000001\t-1.21\t-1\n+0.108\t-1.21\t-1\n 2.18\t1.21\t1\n-0.634\t0.366\t-1\n+0.634\t0.366\t1\n 1.26\t0.799\t-1\n--0.7020000000000001\t-0.8109999999999999\t-1\n+-0.702\t-0.811\t-1\n -0.336\t-0.0523\t1\n--0.7290000000000001\t1.5\t-1\n-1.3\t0.7490000000000001\t-1\n-0.28300000000000003\t0.39399999999999996\t1\n-0.247\t1.65\t-1\n+-0.729\t1.5\t-1\n+1.3\t0.749\t-1\n+0.283\t0.394\t1\n+0.247\t1.65\t1\n 0.212\t1.81\t-1\n-1.08\t-0.628\t1\n+1.08\t-0.628\t-1\n -0.852\t-0.298\t1\n--1.77\t-0.5920000000000001\t1\n+-1.77\t-0.592\t1\n -0.251\t0.327\t1\n-0.41700000000000004\t-1.28\t-1\n+0.417\t-1.28\t-1\n -0.12\t-1.22\t-1\n -2.19\t-1.3\t1\n-2.11\t0.9420000000000001\t1\n+2.11\t0.942\t1\n -0.214\t-0.235\t1\n-1.05\t0.21899999999999997\t-1\n+1.05\t0.219\t-1\n -0.863\t0.174\t1\n 0.244\t1.42\t-1\n 0.0725\t0.596\t1\n--1.34\t0.8690000000000001\t-1\n+-1.34\t0.869\t-1\n -0.0874\t-1.07\t-1\n -0.452\t-1.22\t-1\n 0.973\t0.653\t-1\n-0.9109999999999999\t-0.8320000000000001\t1\n+0.911\t-0.832\t1\n 0.303\t-0.94\t-1\n-0.282\t-0.7609999999999999\t-1\n-1.7\t-0.5539999999999999\t-1\n+0.282\t-0.761\t1\n+1.7\t-0.554\t-1\n 0.659\t1.28\t-1\n--0.192\t0.7909999999999999\t1\n+-0.192\t0.791\t1\n 0.424\t1.64\t1\n -0.59\t-1.04\t-1\n 2.04\t1.36\t1\n--1.11\t-0.35100000000000003\t1\n+-1.11\t-0.351\t1'..b'931\t0.783\t-1\n+0.824\t0.587\t1\n -0.0957\t-1.06\t-1\n-1.05\t0.47200000000000003\t-1\n+1.05\t0.472\t-1\n -0.268\t-1.52\t-1\n-1.35\t0.22899999999999998\t-1\n+1.35\t0.229\t-1\n -1.4\t0.475\t-1\n -1.34\t-0.419\t1\n -0.523\t-1.31\t-1\n-1.18\t1.49\t1\n-0.5660000000000001\t0.0815\t1\n+1.18\t1.49\t-1\n+0.566\t0.0815\t1\n 0.34\t-1.34\t-1\n 0.578\t-0.622\t1\n-0.753\t1.89\t-1\n+0.753\t1.89\t1\n -0.184\t-0.0314\t1\n-0.56\t1.7\t-1\n+0.56\t1.7\t1\n 1.07\t0.457\t-1\n -0.613\t0.775\t1\n-0.8190000000000001\t0.0462\t1\n+0.819\t0.0462\t1\n 1.11\t-0.0628\t-1\n -1.61\t-1.13\t1\n-1.06\t-0.0531\t-1\n+1.06\t-0.0531\t1\n 0.764\t-0.804\t1\n 0.226\t-1.38\t-1\n -1.19\t1.01\t-1\n-1.25\t-0.11800000000000001\t-1\n+1.25\t-0.118\t-1\n -1.76\t-1.17\t1\n--0.23399999999999999\t-0.6559999999999999\t-1\n+-0.234\t-0.656\t1\n -1.45\t-1.29\t1\n-0.23399999999999999\t-0.8220000000000001\t1\n+0.234\t-0.822\t1\n -1.84\t-0.865\t1\n -1.63\t-1.32\t1\n--0.715\t-0.9690000000000001\t-1\n+-0.715\t-0.969\t-1\n 0.0973\t-1.33\t-1\n--0.551\t0.28800000000000003\t1\n-1.39\t-0.013000000000000001\t-1\n+-0.551\t0.288\t1\n+1.39\t-0.013\t-1\n 0.215\t-1.66\t-1\n-0.0224\t1.43\t-1\n--0.33799999999999997\t-1.33\t-1\n+0.0224\t1.43\t1\n+-0.338\t-1.33\t-1\n -0.693\t-0.113\t1\n 0.0533\t-1.02\t-1\n -0.153\t-1.22\t-1\n -1.18\t0.0302\t1\n-1.15\t0.32899999999999996\t-1\n+1.15\t0.329\t-1\n 1.31\t-1.4\t1\n--0.285\t1.98\t1\n-1.06\t-0.0553\t-1\n+-0.285\t1.98\t-1\n+1.06\t-0.0553\t1\n -0.904\t-0.203\t1\n-0.6609999999999999\t-0.19899999999999998\t1\n-0.8959999999999999\t-1.27\t1\n+0.661\t-0.199\t1\n+0.896\t-1.27\t1\n -1.54\t-0.618\t1\n-1.29\t-0.657\t-1\n+1.29\t-0.657\t1\n -1.67\t-1.5\t1\n -1.36\t-0.848\t1\n 1.98\t-0.0252\t-1\n 0.485\t0.635\t-1\n--0.674\t0.8420000000000001\t-1\n+-0.674\t0.842\t-1\n 0.722\t-0.975\t1\n 1.02\t-0.625\t1\n-1.26\t-0.18100000000000002\t-1\n--0.6579999999999999\t-1.31\t-1\n+1.26\t-0.181\t1\n+-0.658\t-1.31\t-1\n -0.405\t-1.25\t-1\n 1.27\t0.493\t-1\n-0.9329999999999999\t-0.27699999999999997\t1\n+0.933\t-0.277\t1\n -0.815\t-0.682\t1\n -1.51\t-0.769\t1\n-0.11699999999999999\t-1.07\t-1\n+0.117\t-1.07\t-1\n 0.384\t2.15\t-1\n -1.32\t1.1\t-1\n 1.2\t-1.65\t1\n 0.0529\t1.52\t-1\n 1.46\t0.0373\t-1\n -0.607\t-1.6\t-1\n--1.06\t-0.5489999999999999\t1\n+-1.06\t-0.549\t1\n -1.39\t0.862\t-1\n 0.527\t0.51\t1\n 1.15\t-0.451\t1\n@@ -721,14 +721,14 @@\n -0.138\t-0.0524\t1\n -0.754\t1.19\t-1\n 0.0574\t-0.134\t1\n-0.877\t0.161\t1\n+0.877\t0.161\t-1\n 1.17\t0.446\t-1\n 0.647\t0.317\t-1\n -1.73\t-0.242\t1\n 0.631\t-0.674\t1\n -0.973\t-0.047\t1\n -0.4\t0.00463\t1\n--1.14\t-1.27\t-1\n+-1.14\t-1.27\t1\n 0.42\t1.1\t-1\n 0.43\t-0.654\t1\n 1.49\t0.365\t-1\n@@ -738,8 +738,8 @@\n -1.22\t-0.0961\t1\n -0.276\t1.05\t-1\n -0.253\t-0.406\t1\n--1.38\t0.6779999999999999\t-1\n--1.13\t-0.44299999999999995\t1\n+-1.38\t0.678\t-1\n+-1.13\t-0.443\t1\n 1.3\t0.175\t-1\n 1.64\t1.46\t1\n 1.48\t1.78\t1\n@@ -748,53 +748,53 @@\n -0.0657\t-1.19\t-1\n -0.653\t0.433\t1\n 2.48\t1.21\t1\n--0.9590000000000001\t1.08\t-1\n-0.8420000000000001\t-0.37200000000000005\t1\n+-0.959\t1.08\t-1\n+0.842\t-0.372\t1\n -0.402\t-1.11\t-1\n--0.29100000000000004\t0.561\t1\n--1.02\t-0.22399999999999998\t1\n-0.45\t-0.10400000000000001\t1\n--1.88\t-0.45399999999999996\t1\n--0.5820000000000001\t-0.752\t-1\n+-0.291\t0.561\t1\n+-1.02\t-0.224\t1\n+0.45\t-0.104\t1\n+-1.88\t-0.454\t1\n+-0.582\t-0.752\t1\n -0.594\t1.24\t-1\n -1.49\t-0.00325\t1\n 0.552\t1.04\t-1\n-1.06\t0.44299999999999995\t-1\n-0.406\t-0.7070000000000001\t1\n-1.15\t0.0436\t-1\n+1.06\t0.443\t-1\n+0.406\t-0.707\t1\n+1.15\t0.0436\t1\n 0.612\t1.37\t-1\n 1.1\t0.508\t-1\n 1.1\t0.604\t-1\n -0.753\t1.18\t-1\n--1.13\t0.41100000000000003\t1\n+-1.13\t0.411\t1\n -0.872\t0.26\t1\n -0.415\t0.256\t1\n-0.8009999999999999\t-0.639\t1\n-0.762\t0.125\t-1\n+0.801\t-0.639\t1\n+0.762\t0.125\t1\n 0.0343\t-1.18\t-1\n 0.524\t-0.231\t1\n -0.0262\t-1.18\t-1\n -1.47\t-0.0358\t1\n 1.29\t0.152\t-1\n--0.851\t0.18899999999999997\t1\n+-0.851\t0.189\t1\n -0.961\t1.0\t-1\n--0.7759999999999999\t0.127\t1\n--0.674\t-0.62\t-1\n-0.244\t-0.69\t-1\n--0.9740000000000001\t0.511\t1\n+-0.776\t0.127\t1\n+-0.674\t-0.62\t1\n+0.244\t-0.69\t1\n+-0.974\t0.511\t1\n 0.37\t1.03\t-1\n -1.98\t-0.88\t1\n-0.308\t0.11699999999999999\t1\n--1.62\t0.46799999999999997\t-1\n+0.308\t0.117\t1\n+-1.62\t0.468\t-1\n -0.843\t-1.08\t-1\n 1.0\t1.17\t-1\n--0.9540000000000001\t0.687\t-1\n+-0.954\t0.687\t1\n 0.768\t-0.966\t1\n 1.64\t1.12\t1\n--1.7\t-0.5539999999999999\t1\n-0.40399999999999997\t0.00999\t1\n-0.7040000000000001\t-0.9059999999999999\t1\n-0.335\t1.39\t-1\n+-1.7\t-0.554\t1\n+0.404\t0.00999\t1\n+0.704\t-0.906\t1\n+0.335\t1.39\t1\n -1.7\t-0.569\t1\n 2.64\t1.14\t1\n 0.769\t0.772\t-1\n'

diff -r 62e3a4e8c54c -r 1c5dcef5ce0f test-data/prediction_multi_lr.tabular
--- a/test-data/prediction_multi_lr.tabular Thu Jan 16 13:49:49 2020 -0500
+++ b/test-data/prediction_multi_lr.tabular Tue May 07 14:11:16 2024 +0000

b'@@ -8,7 +8,7 @@\n -0.14\t-0.06\t2.37\t1.3\t3.4\t4.38\t4.53\t4.71\t2.98\t3.78\t3.86\t4.41\t3.24\t2.09\t1.28\t1.98\t-0.82\t0.8\t0.95\t-2.57\t1.07\t-1.41\t-0.41\t0.86\t1.53\t1.1\t-1.5\t-0.89\t0.6\t-1.44\t0.3\t2.21\t0.82\t1.17\t0.02\t-0.26\t0.38\t-0.17\t-0.11\t1.26\t1\n -0.13\t0.7\t0.56\t1.31\t4.6\t2.7\t5.0\t3.98\t3.41\t2.79\t2.79\t3.39\t0.92\t1.65\t-0.5\t1.85\t-0.81\t-0.14\t1.43\t1.93\t-0.26\t0.1\t-0.05\t-0.41\t1.77\t1.12\t-0.78\t-0.45\t-0.23\t0.08\t0.93\t-0.16\t0.37\t-0.7\t-1.31\t-0.06\t0.93\t0.03\t0.95\t-0.35\t1\n 0.65\t-0.37\t-1.26\t-0.91\t0.99\t1.0\t1.29\t0.39\t0.77\t2.55\t3.53\t4.11\t3.83\t5.63\t4.33\t4.81\t3.12\t2.02\t0.8\t0.16\t0.88\t-2.26\t0.06\t-0.85\t-1.6\t-2.53\t-0.16\t0.4\t-0.95\t0.64\t0.1\t0.35\t-0.16\t0.58\t0.05\t0.47\t1.31\t-1.78\t2.0\t-0.1\t2\n-0.93\t-1.53\t0.26\t0.72\t-1.21\t0.32\t0.12\t1.25\t0.32\t0.43\t0.42\t3.64\t4.09\t6.04\t4.39\t6.27\t3.98\t4.19\t3.59\t0.22\t0.99\t-2.2\t1.02\t0.81\t0.85\t-0.08\t-0.66\t0.23\t-0.53\t0.35\t-1.36\t-0.33\t2.27\t-0.38\t1.12\t0.57\t0.89\t0.17\t1.12\t-0.61\t0\n+0.93\t-1.53\t0.26\t0.72\t-1.21\t0.32\t0.12\t1.25\t0.32\t0.43\t0.42\t3.64\t4.09\t6.04\t4.39\t6.27\t3.98\t4.19\t3.59\t0.22\t0.99\t-2.2\t1.02\t0.81\t0.85\t-0.08\t-0.66\t0.23\t-0.53\t0.35\t-1.36\t-0.33\t2.27\t-0.38\t1.12\t0.57\t0.89\t0.17\t1.12\t-0.61\t2\n 0.82\t1.32\t0.02\t0.16\t-0.36\t-0.03\t1.84\t0.69\t2.08\t3.25\t3.91\t2.69\t4.69\t4.97\t5.19\t3.48\t3.8\t2.02\t0.91\t0.9\t0.98\t1.37\t-0.18\t-0.42\t-0.62\t-0.45\t-0.54\t0.79\t-2.41\t0.72\t0.55\t0.18\t0.32\t0.64\t1.04\t-0.54\t-1.02\t1.21\t-1.21\t-0.74\t2\n 0.49\t-0.37\t-0.66\t1.68\t2.33\t1.92\t4.09\t2.12\t3.36\t4.43\t4.05\t5.14\t3.01\t2.17\t0.45\t0.91\t0.14\t-0.25\t1.73\t0.3\t-0.64\t-0.18\t-0.73\t-0.49\t1.56\t0.45\t0.25\t0.76\t1.19\t-1.15\t1.0\t-1.04\t-1.8\t0.19\t1.86\t-0.93\t-0.04\t-0.72\t-1.45\t-0.4\t1\n -0.87\t0.29\t-0.34\t1.68\t-1.19\t1.91\t-0.02\t0.34\t1.47\t3.47\t3.31\t3.51\t3.26\t0.65\t4.14\t0.69\t1.47\t1.37\t1.43\t0.18\t0.25\t1.68\t1.81\t0.74\t-1.27\t0.54\t-0.51\t-0.02\t0.31\t1.32\t0.6\t0.44\t-0.06\t-1.42\t-1.34\t-1.87\t1.97\t-0.21\t-0.32\t-0.67\t2\n@@ -25,7 +25,7 @@\n 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-1.28\t1.61\t1.8\t1.18\t2.92\t3.99\t5.19\t6.06\t2.53\t5.42\t0.39\t1.99\t2.85\t-0.21\t1.13\t-1.29\t-0.85\t-1.17\t-0.06\t0.87\t-0.65\t0.91\t-0.38\t0.01\t-0.42\t-0.05\t-0.02\t0.12\t0.07\t-0.2\t1.19\t-1.09\t1.11\t-0.71\t0.18\t0.21\t-0.87\t-1.13\t0.58\t0.56\t1\n--0.28\t-0.32\t3.28\t3.63\t2.39\t4.16\t5.85\t4.11\t4.51\t3.91\t2.26\t1.53\t0.93\t1.8\t1.84\t1.04\t-0.75\t0.99\t1.03\t-0.73\t-0.75\t0.86\t-1.76\t0.89\t0.01\t-0.33\t0.53\t-0.95\t0.33\t-0.64\t-1.11\t-0.19\t0.0\t-0.04\t1.47\t0.92\t-0.27\t0.09\t0.39\t0.31\t1\n+-0.28\t-0.32\t3.28\t3.63\t2.39\t4.16\t5.85\t4.11\t4.51\t3.91\t2.26\t1.53\t0.93\t1.8\t1.84\t1.04\t-0.75\t0.99\t1.03\t-0.73\t-0.75\t0.86\t-1.76\t0.89\t0.01\t-0.33\t0.53\t-0.95\t0.33\t-0.64\t-1.11\t-0.19\t0.0\t-0.04\t1.47\t0.92\t-0.27\t0.09\t0.39\t0.31\t0\n 1.95\t-0.27\t0.79\t0.83\t-0.52\t-0.14\t1.51\t1.1\t1.09\t1.28\t3.25\t4.02\t1.79\t3.88\t4.22\t4.26\t3.21\t3.81\t2.57\t1.81\t-1.22\t-0.26\t0.87\t2.08\t-0.86\t-0.22\t-0.3\t0.63\t0.04\t-0.14\t-0.49\t0.29\t-1.41\t-0.54\t0.41\t0.52\t-0.57\t-0.28\t0.57\t-2.54\t2\n -1.12\t-0.29\t1.44\t0.71\t0.75\t-0.66\t1.15\t0.33\t-1.42\t1.27\t2.1\t2.25\t3.08\t4.61\t6.39\t4.33\t5.0\t4.96\t0.48\t0.56\t-0.08\t-0.11\t0.09\t-0.17\t-0.39\t1.76\t-0.85\t-2.34\t0.4\t0.14\t-2.0\t-1.35\t-0.81\t2.45\t-0.41\t-0.99\t-0.04\t0.9\t-1.37\t0.66\t0\n -0.47\t0.11\t-0.39\t-0.07\t1.37\t1.64\t3.57\t2.79\t3.96\t6.18\t3.21\t4.48\t1.91\t0.11\t2.88\t-0.88\t0.09\t-0.02\t0.57\t1.46\t0.22\t-0.14\t1.25\t0.17\t0.97\t-1.52\t1.27\t0.59\t-0.77\t0.38\t0.29\t0.44\t-1.32\t-0.26\t0.75\t-1.89\t0.44\t-0.94\t-3.03\t-0.01\t1\n@@ -62,17 +62,17 @@\n 0.33\t-0.65\t0.18\t0.15\t1.42\t-0.92\t1.2\t0.76\t1.57\t1.66\t2.26\t3.71\t3.8\t4.72\t4.95\t3.02\t3.79\t2.55\t2.01\t-0.12\t0.41\t1.13\t-0.33\t-2.09\t-0.89\t0.72\t-0.03\t-1.31\t-1.32\t0.0\t1.2\t0.86\t-0.44\t1.5\t1.55\t0.81\t0.9\t1.37\t0.34\t1.2\t2\n -2.36\t0.56\t0.69\t-0.88\t-0.45\t1.0\t-0.77\t1.39\t4.21\t3.88\t4.44\t3.43\t3.13\t5.82\t2.14\t2.49\t2.5\t1.65\t0.86\t1.43\t0.92\t-0.38\t0.61\t0.11\t0.4\t-0.2\t0.17\t-1.05\t0.38\t0.5\t-0.21\t1.44\t0.56\t-0.13\t-0.35\t-2.08\t0.45\t0.24\t-1.13\t0.1\t2\n 0.71\t-0.15\t-1.91\t2.01\t-0.34\t-0.31\t0.78\t1.73\t0.37\t0.01\t2.12\t3.61\t6.2\t2.54\t7.79\t4.81\t3.22\t2.44\t2.53\t1.27\t-0.77\t1.48\t-1.'..b'44\t0.31\t-0.41\t-1.58\t1.55\t-0.61\t0.15\t-0.86\t1.84\t-0.82\t0.81\t-0.41\t-0.27\t-0.21\t-1.87\t1.61\t-0.33\t1.45\t-0.84\t-1.57\t-0.99\t-0.87\t1.38\t1\n 0.69\t-1.06\t-0.08\t0.24\t0.93\t0.93\t-0.45\t2.71\t1.5\t3.02\t5.01\t5.1\t5.84\t3.12\t4.4\t5.13\t1.47\t2.38\t0.56\t-0.21\t-0.87\t0.41\t0.83\t0.06\t0.76\t-0.54\t0.88\t0.33\t0.33\t-0.41\t-1.14\t1.14\t1.1\t0.53\t-0.14\t0.96\t-0.69\t-0.26\t1.54\t-1.27\t2\n 1.19\t1.74\t2.69\t3.21\t4.21\t4.37\t5.69\t4.94\t4.93\t3.49\t1.18\t1.86\t-0.59\t-0.6\t-0.17\t-1.88\t-0.84\t-1.43\t0.25\t0.6\t0.65\t-1.32\t-0.99\t0.0\t-0.57\t0.03\t1.45\t0.15\t-0.84\t0.59\t-2.1\t0.95\t0.55\t-0.86\t-0.26\t-0.35\t-0.97\t0.72\t2.1\t-2.23\t1\n@@ -474,7 +474,7 @@\n 0.81\t-0.31\t3.05\t2.71\t4.48\t4.43\t3.64\t3.55\t1.97\t1.94\t2.01\t1.19\t0.38\t0.93\t2.14\t0.28\t-1.68\t1.26\t0.78\t0.59\t0.32\t1.25\t-1.62\t-1.96\t-1.04\t-0.52\t-1.65\t0.44\t0.66\t-0.37\t0.25\t0.08\t0.36\t-1.34\t-0.29\t-0.55\t-0.7\t0.49\t1.35\t-0.28\t0\n 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0.46\t0.24\t1.8\t0.64\t2.06\t3.27\t4.43\t3.71\t4.96\t3.71\t3.41\t2.78\t1.15\t1.09\t0.8\t0.48\t0.49\t0.75\t0.73\t0.01\t2.03\t0.27\t0.17\t1.24\t0.08\t-0.29\t1.31\t0.38\t0.38\t0.27\t-0.07\t0.68\t0.89\t0.23\t0.86\t-1.3\t-0.98\t-1.15\t-0.5\t0.43\t1\n-0.66\t0.57\t0.18\t0.44\t1.34\t1.31\t0.37\t2.79\t3.46\t5.32\t6.22\t4.41\t4.11\t4.09\t1.74\t0.38\t0.07\t0.35\t-0.72\t-0.33\t0.68\t0.12\t-0.49\t-0.74\t-0.39\t-0.26\t-1.24\t0.92\t0.84\t0.05\t-0.66\t1.72\t0.26\t0.92\t1.44\t-0.26\t-0.19\t-0.56\t1.25\t-0.21\t1\n+0.66\t0.57\t0.18\t0.44\t1.34\t1.31\t0.37\t2.79\t3.46\t5.32\t6.22\t4.41\t4.11\t4.09\t1.74\t0.38\t0.07\t0.35\t-0.72\t-0.33\t0.68\t0.12\t-0.49\t-0.74\t-0.39\t-0.26\t-1.24\t0.92\t0.84\t0.05\t-0.66\t1.72\t0.26\t0.92\t1.44\t-0.26\t-0.19\t-0.56\t1.25\t-0.21\t2\n 0.12\t1.81\t2.33\t2.01\t3.74\t4.68\t3.95\t6.02\t4.59\t4.01\t1.05\t1.34\t1.21\t2.97\t-1.8\t-0.06\t-0.93\t-0.44\t1.1\t0.01\t0.36\t-0.47\t0.13\t0.42\t-1.54\t1.11\t-0.21\t0.32\t2.1\t-0.82\t-1.65\t-0.53\t0.33\t2.32\t-1.81\t1.15\t-1.03\t0.24\t-0.1\t0.42\t1\n 0.19\t-0.15\t-0.03\t-1.57\t0.25\t0.1\t1.36\t0.76\t1.3\t2.01\t3.03\t4.29\t3.2\t4.7\t4.98\t3.8\t3.15\t2.3\t2.36\t1.9\t-1.25\t-0.6\t-0.93\t-0.6\t-0.45\t1.02\t-0.16\t0.28\t0.78\t1.06\t0.46\t0.08\t-1.08\t-0.94\t-1.71\t-0.23\t0.5\t0.8\t1.91\t-0.67\t2\n -0.76\t0.25\t0.81\t-1.06\t0.45\t1.82\t3.6\t2.92\t3.79\t4.72\t2.79\t2.73\t2.59\t2.94\t2.16\t1.04\t-2.49\t0.75\t-1.42\t-0.17\t-0.72\t0.62\t0.31\t-0.12\t-1.51\t-1.16\t0.12\t0.86\t-0.56\t1.16\t-0.47\t0.14\t-0.87\t-0.34\t0.37\t0.38\t-1.17\t1.54\t1.64\t1.2\t1\n@@ -483,7 +483,7 @@\n 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2.58\t-0.75\t-1.64\t0.03\t0.5\t2.67\t3.02\t1.9\t1.84\t3.56\t0.61\t3.54\t1.82\t2.43\t3.04\t2.17\t1.5\t1.6\t0.97\t0.19\t1.06\t-0.15\t2.41\t0.09\t-0.52\t-0.65\t0.21\t-1.56\t-1.03\t-0.91\t1.46\t-0.77\t0.51\t-1.59\t0.31\t0.08\t-0.59\t0.5\t-0.94\t1.08\t0\n--0.09\t-1.11\t1.96\t0.58\t1.45\t3.25\t2.2\t5.79\t3.37\t1.09\t2.75\t1.59\t1.47\t2.46\t-0.48\t0.98\t1.22\t2.32\t2.11\t-0.55\t-0.15\t0.16\t-0.15\t-0.8\t-0.57\t-1.03\t1.21\t-0.54\t-0.52\t-1.6\t1.76\t-1.11\t0.64\t2.4\t1.16\t-0.31\t-0.42\t-0.79\t0.99\t-1.35\t0\n+-0.09\t-1.11\t1.96\t0.58\t1.45\t3.25\t2.2\t5.79\t3.37\t1.09\t2.75\t1.59\t1.47\t2.46\t-0.48\t0.98\t1.22\t2.32\t2.11\t-0.55\t-0.15\t0.16\t-0.15\t-0.8\t-0.57\t-1.03\t1.21\t-0.54\t-0.52\t-1.6\t1.76\t-1.11\t0.64\t2.4\t1.16\t-0.31\t-0.42\t-0.79\t0.99\t-1.35\t1\n -2.23\t-0.62\t-0.6\t1.86\t2.54\t2.67\t1.92\t0.74\t0.09\t1.58\t1.57\t3.16\t3.75\t1.8\t1.51\t2.23\t4.31\t1.06\t-0.28\t1.39\t0.81\t-1.17\t-0.96\t-0.7\t-1.4\t0.44\t1.14\t-1.99\t0.37\t-0.63\t-0.49\t-0.77\t-0.62\t-0.39\t-0.44\t0.68\t0.33\t-0.81\t0.65\t1.28\t0\n 1.23\t2.65\t-0.63\t1.25\t-1.09\t-0.14\t-0.48\t0.3\t0.93\t1.9\t2.63\t3.42\t2.95\t3.71\t5.38\t2.95\t3.93\t2.6\t0.8\t0.97\t0.24\t1.83\t0.69\t-3.43\t-2.33\t2.35\t0.66\t0.01\t-0.83\t-0.76\t-0.23\t0.25\t0.19\t-0.05\t-1.34\t-0.69\t0.05\t-0.77\t0.67\t-0.19\t2\n -0.52\t0.88\t1.07\t0.61\t-1.37\t1.05\t0.64\t2.05\t1.54\t0.44\t3.73\t2.08\t5.23\t2.78\t4.91\t2.12\t3.14\t1.56\t3.4\t1.08\t1.49\t-0.68\t0.41\t-0.82\t-0.4\t0.11\t-0.63\t-0.81\t-1.17\t-0.63\t-0.67\t1.42\t-0.45\t0.11\t0.56\t-0.48\t0.21\t-0.8\t-0.33\t-0.14\t2\n'

diff -r 62e3a4e8c54c -r 1c5dcef5ce0f test-data/prf_binary_knn.html
--- a/test-data/prf_binary_knn.html Thu Jan 16 13:49:49 2020 -0500
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000

[

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diff -r 62e3a4e8c54c -r 1c5dcef5ce0f test-data/prf_binary_linearsvm.html
--- a/test-data/prf_binary_linearsvm.html Thu Jan 16 13:49:49 2020 -0500
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000

[

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diff -r 62e3a4e8c54c -r 1c5dcef5ce0f test-data/prf_binary_rfc.html
--- a/test-data/prf_binary_rfc.html Thu Jan 16 13:49:49 2020 -0500
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000

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diff -r 62e3a4e8c54c -r 1c5dcef5ce0f test-data/prf_binary_sgd.html
--- a/test-data/prf_binary_sgd.html Thu Jan 16 13:49:49 2020 -0500
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000

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diff -r 62e3a4e8c54c -r 1c5dcef5ce0f test-data/prf_multi_lr.html
--- a/test-data/prf_multi_lr.html Thu Jan 16 13:49:49 2020 -0500
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000

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diff -r 62e3a4e8c54c -r 1c5dcef5ce0f test-data/roc_auc_binary_knn.html
--- a/test-data/roc_auc_binary_knn.html Thu Jan 16 13:49:49 2020 -0500
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000

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diff -r 62e3a4e8c54c -r 1c5dcef5ce0f test-data/roc_auc_binary_linearsvm.html
--- a/test-data/roc_auc_binary_linearsvm.html Thu Jan 16 13:49:49 2020 -0500
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000

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diff -r 62e3a4e8c54c -r 1c5dcef5ce0f test-data/roc_auc_binary_rfc.html
--- a/test-data/roc_auc_binary_rfc.html Thu Jan 16 13:49:49 2020 -0500
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000

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diff -r 62e3a4e8c54c -r 1c5dcef5ce0f test-data/roc_auc_binary_sgd.html
--- a/test-data/roc_auc_binary_sgd.html Thu Jan 16 13:49:49 2020 -0500
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000

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diff -r 62e3a4e8c54c -r 1c5dcef5ce0f test-data/roc_auc_multi_lr.html
--- a/test-data/roc_auc_multi_lr.html Thu Jan 16 13:49:49 2020 -0500
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000

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