diff --git a/Part 3 - Classification/Section 21 - Evaluating Classification Models Performance/README.md b/Part 3 - Classification/Section 21 - Evaluating Classification Models Performance/README.md index 9ec18c7..36feb2f 100644 --- a/Part 3 - Classification/Section 21 - Evaluating Classification Models Performance/README.md +++ b/Part 3 - Classification/Section 21 - Evaluating Classification Models Performance/README.md @@ -12,4 +12,13 @@ Accuracy increases, although we did not train. So accuarcy cannot be always trus #CAP: Cummulative Accuracy Profile. Greater area under the curve, the better is the model. -![](cap.png) \ No newline at end of file +![](cap.png) + +ap = area between the perfect model and random model. +ar = area between the good model and random model. + +Accuracy Ratio =(AR) ap / ar. +AR closer to one better is the model. +![](cm1.png) + +Other option is to draw a 50% line and see where it touches our model(good model) on the y-axis and then make judgement accordingly. \ No newline at end of file diff --git a/Part 3 - Classification/Section 21 - Evaluating Classification Models Performance/cm1.png b/Part 3 - Classification/Section 21 - Evaluating Classification Models Performance/cm1.png new file mode 100644 index 0000000..52d1e62 Binary files /dev/null and b/Part 3 - Classification/Section 21 - Evaluating Classification Models Performance/cm1.png differ