Hi,
I am using Svm, random forest, decision trees and neural network and comparing performance of models.
Could anyone please tell me how can I calculate f-score, recall and precision of each of these models?
Regards
By "f-score", are you talking about the traditional F-measure or balanced F-score (F1 score) which is the harmonic mean of precision and recall or are you referring to an F-test statistic of some sort? SAS Enterprise Miner calculates precision defined as % true predicted events / (true predicted + false predicted) and recall defined as the event classification rate. It is likely you could compute this statistic relatively easily but I am not aware of anything by that name being generated by SAS Enterprise Miner. Do you have a formula for the f-score you wish to compute?
Cordially,
Doug
By "f-score", are you talking about the traditional F-measure or balanced F-score (F1 score) which is the harmonic mean of precision and recall or are you referring to an F-test statistic of some sort? SAS Enterprise Miner calculates precision defined as % true predicted events / (true predicted + false predicted) and recall defined as the event classification rate. It is likely you could compute this statistic relatively easily but I am not aware of anything by that name being generated by SAS Enterprise Miner. Do you have a formula for the f-score you wish to compute?
Cordially,
Doug
Available on demand!
Missed SAS Innovate Las Vegas? Watch all the action for free! View the keynotes, general sessions and 22 breakouts on demand.
Use this tutorial as a handy guide to weigh the pros and cons of these commonly used machine learning algorithms.
Find more tutorials on the SAS Users YouTube channel.