Mercurial > repos > bgruening > sklearn_stacking_ensemble_models
comparison ml_visualization_ex.py @ 4:17f173a4a745 draft
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 02087ce2966cf8b4aac9197a41171e7f986c11d1-dirty"
| author | bgruening | 
|---|---|
| date | Wed, 02 Oct 2019 03:28:39 -0400 | 
| parents | 963e449636d3 | 
| children | 00819b7f2f55 | 
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| 3:963e449636d3 | 4:17f173a4a745 | 
|---|---|
| 144 | 144 | 
| 145 if len(df1.columns) > 1: | 145 if len(df1.columns) > 1: | 
| 146 precision["micro"], recall["micro"], _ = precision_recall_curve( | 146 precision["micro"], recall["micro"], _ = precision_recall_curve( | 
| 147 df1.values.ravel(), df2.values.ravel(), pos_label=pos_label) | 147 df1.values.ravel(), df2.values.ravel(), pos_label=pos_label) | 
| 148 ap['micro'] = average_precision_score( | 148 ap['micro'] = average_precision_score( | 
| 149 df1.values, df2.values, average='micro', pos_label=pos_label or 1) | 149 df1.values, df2.values, average='micro', | 
| 150 pos_label=pos_label or 1) | |
| 150 | 151 | 
| 151 data = [] | 152 data = [] | 
| 152 for key in precision.keys(): | 153 for key in precision.keys(): | 
| 153 trace = go.Scatter( | 154 trace = go.Scatter( | 
| 154 x=recall[key], | 155 x=recall[key], | 
| 199 name='%s (area = %.2f)' % (key, roc_auc[key]) if key == 'micro' | 200 name='%s (area = %.2f)' % (key, roc_auc[key]) if key == 'micro' | 
| 200 else 'column %s (area = %.2f)' % (key, roc_auc[key]) | 201 else 'column %s (area = %.2f)' % (key, roc_auc[key]) | 
| 201 ) | 202 ) | 
| 202 data.append(trace) | 203 data.append(trace) | 
| 203 | 204 | 
| 204 trace = go.Scatter(x=[0, 1], y=[0, 1], | 205 trace = go.Scatter(x=[0, 1], y=[0, 1], | 
| 205 mode='lines', | 206 mode='lines', | 
| 206 line=dict(color='black', dash='dash'), | 207 line=dict(color='black', dash='dash'), | 
| 207 showlegend=False) | 208 showlegend=False) | 
| 208 data.append(trace) | 209 data.append(trace) | 
| 209 | 210 | 
