# HG changeset patch # User bgruening # Date 1570003023 14400 # Node ID 7388ffedf12c3e12d2e05e05c4e0faeae53bad0d # Parent 653be9c354ecfd95416c667df21fec3faa7c74fd "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 02087ce2966cf8b4aac9197a41171e7f986c11d1-dirty" diff -r 653be9c354ec -r 7388ffedf12c main_macros.xml --- a/main_macros.xml Fri Sep 13 12:22:41 2019 -0400 +++ b/main_macros.xml Wed Oct 02 03:57:03 2019 -0400 @@ -421,27 +421,46 @@ - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff -r 653be9c354ec -r 7388ffedf12c ml_visualization_ex.py --- a/ml_visualization_ex.py Fri Sep 13 12:22:41 2019 -0400 +++ b/ml_visualization_ex.py Wed Oct 02 03:57:03 2019 -0400 @@ -146,7 +146,8 @@ precision["micro"], recall["micro"], _ = precision_recall_curve( df1.values.ravel(), df2.values.ravel(), pos_label=pos_label) ap['micro'] = average_precision_score( - df1.values, df2.values, average='micro', pos_label=pos_label or 1) + df1.values, df2.values, average='micro', + pos_label=pos_label or 1) data = [] for key in precision.keys(): @@ -201,7 +202,7 @@ ) data.append(trace) - trace = go.Scatter(x=[0, 1], y=[0, 1], + trace = go.Scatter(x=[0, 1], y=[0, 1], mode='lines', line=dict(color='black', dash='dash'), showlegend=False) diff -r 653be9c354ec -r 7388ffedf12c stacking_ensembles.py --- a/stacking_ensembles.py Fri Sep 13 12:22:41 2019 -0400 +++ b/stacking_ensembles.py Wed Oct 02 03:57:03 2019 -0400 @@ -11,7 +11,7 @@ from sklearn import ensemble from galaxy_ml.utils import (load_model, get_cv, get_estimator, - get_search_params) + get_search_params) warnings.filterwarnings('ignore')