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support for multiclass output prob

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tqchen
2014-08-01 11:21:17 -07:00
parent 8b4f7d7fa2
commit 662733db31
4 changed files with 36 additions and 7 deletions
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7
demo/multiclass_classification/train.py
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@@ -39,4 +39,11 @@ pred = bst.predict( xg_test );
print ('predicting, classification error=%f' % (sum( int(pred[i]) != test_Y[i] for i in range(len(test_Y))) / float(len(test_Y)) ))
# do the same thing again, but output probabilities
param['objective'] = 'multi:softprob'
bst = xgb.train(param, xg_train, num_round, watchlist );
# get prediction, this is in 1D array, need reshape to (nclass, ndata)
yprob = bst.predict( xg_test ).reshape( 6, test_Y.shape[0] )
ylabel = np.argmax( yprob, axis=0)
print ('predicting, classification error=%f' % (sum( int(ylabel[i]) != test_Y[i] for i in range(len(test_Y))) / float(len(test_Y)) ))