Tag: precision-recall

Mismatch of manual computation of a evaluation metrics with Sklearn functions

classification machine-learning precision-recall python scikit-learn

I wanted to compare the manual computations of the precision and recall with scikit-learn functions. However, recall_score() and precision_score() of scikit-learn functions gave me different results. Not sure why! Could you please give me some advice why I am getting different results? Thanks! My confusion matrix: Answer It should be (check return value’s ordering): Please refer: here

precision score warnings results in score =0 sklearn

machine-learning precision-recall python scikit-learn

I am using precision_score in sklearn to evaluate the result of the outlier detection algorithm. I trained with one class only and predict on unseen data. So the label for the one class is just 0 all the way. I have found the following: There are two columns, truth and predicted. (I used the label encoder to beautify the number,