How to find the Precision, Recall, Accuracy using SVM?
libsvm, machine-learning, scikit-learn, svm
Solution
These performance measures are easy to obtain from the predicted labels and true labels, as a post-processing step:
- Precision = TP / (TP+FP)
- Recall = TP / (TP+FN)
- Accuracy = (TP + TN) / (TP + TN + FP + FN)
With TP, FP, TN, FN being number of true positives, false positives, true negatives and false negatives, respectively.
Problem
Duplicate calculating Precision, Recall and F Score I have a input file with text description and classified level (i.e.levelA and levelB). I want to write a SVM classifier that measure precision, recall and accuracy. I looked at scikit and LIBSVM but I want to know more step by step. Any sample code or basic tutorial would be really nice. Thanks for any suggestion in advance.