Mercurial > repos > bgruening > sklearn_model_validation
comparison ml_visualization_ex.py @ 21:887e0aaa482e draft
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 02087ce2966cf8b4aac9197a41171e7f986c11d1-dirty"
author | bgruening |
---|---|
date | Wed, 02 Oct 2019 04:06:01 -0400 |
parents | 5895fe0b8bde |
children | a5aed87b2cc0 |
comparison
equal
deleted
inserted
replaced
20:5895fe0b8bde | 21:887e0aaa482e |
---|---|
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 |