From e8fbd0b6fe51888452584f80fac8508b1ba8ab3c Mon Sep 17 00:00:00 2001 From: gebele Date: Thu, 27 Jun 2019 14:13:29 +0000 Subject: use accept value for rates --- views/model_details.haml | 17 +++++++++-------- 1 file changed, 9 insertions(+), 8 deletions(-) diff --git a/views/model_details.haml b/views/model_details.haml index d70a7e6..0f34632 100644 --- a/views/model_details.haml +++ b/views/model_details.haml @@ -48,21 +48,22 @@ %p.card-text - if model.classification? / accuracy, confusion matrixes + - av = cv.accept_values - keys = cv.accuracy.collect{|key, value| key} - acc = cv.accuracy.collect{|key, value| value.signif(3)} - - tpr = cv.true_rate.collect{|key, hash| hash[cv.accept_values[0]].signif(3)} - - fpr = cv.true_rate.collect{|key, hash| hash[cv.accept_values[1]].signif(3)} - - pp = cv.predictivity.collect{|key, hash| hash[cv.accept_values[0]].signif(3)} - - np = cv.predictivity.collect{|key, hash| hash[cv.accept_values[1]].signif(3)} + - tpr = cv.true_rate.collect{|key, hash| hash[av[0]].signif(3)} + - fpr = cv.true_rate.collect{|key, hash| hash[av[1]].signif(3)} + - pp = cv.predictivity.collect{|key, hash| hash[av[0]].signif(3)} + - np = cv.predictivity.collect{|key, hash| hash[av[1]].signif(3)} %table.table.table-borderless.table-responsive %tr %td.text-right = "Nr.#{idx+1}" %td.text-center.fit Accuracy: - %td.text-right.fit True positive rate: - %td.text-right.fit True negative rate: - %td.text-right.fit Positive predictiv value: - %td.text-right.fit Negative predictiv value: + %td.text-right.fit True rate #{av[0]}: + %td.text-right.fit True rate #{av[1]}: + %td.text-right.fit #{av[0]} predictiv value: + %td.text-right.fit #{av[1]} predictiv value: / mimic vertical line %td.border-right %td.text-center.fit Confusion matrix all: -- cgit v1.2.3