Folks, I sometimes hear complains related to metrics and its clearness for end-users.
Would you add a couple of words related to each value to wiki/readme.io? чт, 13 дек. 2018 г. в 17:13, Alexey Zinoviev <zaleslaw....@gmail.com>: > So, I agree that we should avoid ineffective metrics calculations. > I think that in 2.8 release we should have > > 1. BinaryClassificationMetric with all metrics from Wikipedia > 2. Metric interface with 1 or two implementations in example folder or > in metric package like roc auc and accuracy > 3. BinaryClassificationMetric and MultiClassClassificationMetrics should > implement new interface MetricGroup > > Will totally change the current PR according your recommendation > > чт, 13 дек. 2018 г. в 16:06, Алексей Платонов <aplaton...@gmail.com>: > > > You can compute just TP (true-positive), FP, TN and FN counters and use > > them to evaluate Recall, Precision, Accuracy, ect. If you want to specify > > class for Pr evaluation, then you can compute Pr for first label as > > TP/(TP+FP) and for second label as TN/(TN+FN) for example. After it we > can > > unite all one-point metrics evaluation. > > > > In my opinion we can redesign metrics calculation and provide one-point > > metrics (like Pr, Re) and integral metrics like ROC AUC where one-point > > metrics can be calculated through TP,FP etc. > > > > Maybe you should design class BinaryClassificationMetric that computes > > these counters and provide methods like recall :: () -> double, precision > > :: () -> double, etc. > > > > чт, 13 дек. 2018 г. в 13:26, Yuriy Babak <y.ch...@gmail.com>: > > > > > Igniters, Alexey > > > > > > I want to discuss the ticket 10371 [1], currently, we calculate 4 > numbers > > > (true positive, true negative, false positive, false negative) for each > > > "point metric" like accuracy, recall, f-score and precision for each > > label. > > > > > > So for the full score we need calculates those 4 numbers 8 times. But > we > > > could calculate all 8 metrics(4 for the first label and 4 for the > second > > > label). > > > > > > I suggest introducing new API "point metric" for metrics like those > > > 4(accuracy, recall, f-score, and precision) and "integral metric" for > > > metrics like ROC AUC [2]. > > > > > > Any thoughts would be appreciated. > > > > > > [1] - https://issues.apache.org/jira/browse/IGNITE-10371 > > > [2] - https://issues.apache.org/jira/browse/IGNITE-10145 > > > > > >
