Sklearn metrics for multiclass classification
I have performed GaussianNB classification using a sklearn. I tried to calculate the metrics using the following code:
print accuracy_score(y_test, y_pred)
print precision_score(y_test, y_pred)
Accuracy score is working correctly but the precision score calculation is showing error as:
ValueError: Target is multiclass but average='binary'. Please choose another average setting.
As the target is multiclass, can I have the metric scores of precision, recall, etc.?
Top keyword - target is multiclass but average='binary'. please choose another average setting.
In your code, notice that the
precision_score(y_test, y_pred)is equivalent to
precision_score(y_test, y_pred, pos_label=1, average='binary').'binary':
Their report results for the class are specified by pos_label. This is applicable only if targets (y_{true,pred}) are binary.
To solve target is multiclass but average='binary'. please choose another average setting here labels are not binary, but probably one-hot encoded. There are other options which should work with your data:
For example:
precision_score(y_test, y_pred, average=None)will return the precision scores for each class, while
precision_score(y_test, y_pred, average='micro')will return the total ratio of tp/(tp + fp)
The pos_label argument will be ignored if you choose another average option than binary.