cancel
Showing results for 
Show  only  | Search instead for 
Did you mean: 
%3CLINGO-SUB%20id%3D%22lingo-sub-213304%22%20slang%3D%22en-US%22%20mode%3D%22NONE%22%3E%E4%BA%A4%E5%8F%89%E9%A9%97%E8%AD%89%E6%B7%B7%E6%B7%86%E7%9F%A9%E9%99%A3%E6%87%89%E5%8C%85%E6%8B%AC%E6%89%80%E6%9C%89%E4%BA%A4%E5%8F%89%E9%A9%97%E8%AD%89%E7%9A%84%E6%95%B8%E6%93%9A%EF%BC%8C%E8%80%8C%E4%B8%8D%E5%83%85%E5%83%85%E6%98%AF%E6%9C%80%E5%BE%8C%E4%B8%80%E5%80%8B%3C%2FLINGO-SUB%3E%3CLINGO-BODY%20id%3D%22lingo-body-213304%22%20slang%3D%22en-US%22%20mode%3D%22NONE%22%3E%3CP%3E%E5%85%B7%E6%9C%89%E4%BA%8C%E9%80%B2%E5%88%B6Y%E7%9A%84%E9%A0%90%E6%B8%AC%E6%A8%A1%E5%9E%8B%E5%85%81%E8%A8%B1%E4%BA%A4%E5%8F%89%E9%A9%97%E8%AD%89%EF%BC%88%E4%BE%8B%E5%A6%82k%E5%80%8D%E6%88%96%E9%81%BA%E6%BC%8F%E4%B8%80%E5%80%8B%EF%BC%89%EF%BC%8C%E6%B7%B7%E6%B7%86%E7%9F%A9%E9%99%A3%E5%83%85%E5%8F%8D%E6%98%A0%E4%BA%A4%E5%8F%89%E5%88%86%E9%A1%9E%E7%9A%84%E6%9C%80%E5%BE%8C%E4%B8%80%E6%AC%A1%E8%BF%AD%E4%BB%A3%E3%80%82%E4%BE%8B%E5%A6%82%EF%BC%8C%E5%9C%A85%E5%80%8D%E4%BA%A4%E5%8F%89%E9%A9%97%E8%AD%89%E4%B8%AD%EF%BC%8C%E8%A8%93%E7%B7%B4%E9%9B%86%E6%93%81%E6%9C%8980%EF%BC%85%E7%9A%84%E6%95%B8%E6%93%9A%EF%BC%8C%E8%80%8C%E9%A9%97%E8%AD%89%E9%9B%86%E5%89%87%E9%A1%AF%E7%A4%BA20%EF%BC%85%E3%80%82%26nbsp%3B%20%E9%A9%97%E8%AD%89%E9%9B%86%E6%87%89%E5%90%88%E4%BD%B5%E6%89%80%E6%9C%895%E6%8A%98%E6%95%B8%E6%93%9A%E4%BB%A5%E9%A1%AF%E7%A4%BA100%EF%BC%85%E3%80%82%26nbsp%3B%20%E5%A6%82%E6%9E%9C%E9%81%BA%E6%BC%8F%E4%B8%80%E5%80%8B%EF%BC%8C%E5%89%87%E9%A9%97%E8%AD%89%E9%9B%86%E5%8F%AA%E6%9C%89%E4%B8%80%E5%80%8B%E8%A7%80%E5%AF%9F%E7%B5%90%E6%9E%9C%EF%BC%8C%E5%AE%83%E7%94%9A%E8%87%B3%E6%9B%B4%E6%B2%92%E6%9C%89%E7%94%A8%E3%80%82%26nbsp%3B%26nbsp%3B%3C%2FP%3E%3C%2FLINGO-BODY%3E%3CLINGO-LABS%20id%3D%22lingo-labs-213304%22%20slang%3D%22en-US%22%20mode%3D%22NONE%22%3E%3CLINGO-LABEL%3E%E7%B5%B1%E8%A8%88%E8%88%87%E5%88%86%E6%9E%90%3C%2FLINGO-LABEL%3E%3C%2FLINGO-LABS%3E
Choose Language Hide Translation Bar

cross validation confusion matrix should include all cross validated data not just last

Predictive models with binary Y that allow cross validation, eg k-fold or leave one out, the confusion matrix reflect only the last iteration of the cross classification. For example in 5-fold cross validation the training set has 80% of the data and the Validation set shows 20%.  The validation set should combine all 5 folds of the data to show 100%.  For leave one out it is even more useless as the validation set only has a single observation.  

1 Comment
Ryan_Gilmore
Community Manager
Status changed to: Archived
We are archiving this request. If this is still important please comment with additional details and we will reopen. Thank you!