roc

信息检索(IR)的评价指标介绍

扶醉桌前 提交于 2019-12-09 12:52:32
准确率、召回率、F1 信息检索、分类、识别、翻译等领域两个最基本指标是召回率(Recall Rate)和准确率(Precision Rate),召回率也叫查全率,准确率也叫查准率,概念公式: 召回率(Recall) = 系统检索到的相关文件 / 系统所有相关的文件总数 准确率(Precision) = 系统检索到的相关文件 / 系统所有检索到的文件总数 图示表示如下: 注意:准确率和召回率是互相影响的,理想情况下肯定是做到两者都高,但是一般情况下准确率高、召回率就低,召回率低、准确率高,当然如果两者都低,那是什么地方出问题了。一般情况,用不同的阀值,统计出一组不同阀值下的精确率和召回率,如下图

Plotting a linear discriminant analysis, classification tree and Naive Bayes Curve on a single ROC plot

女生的网名这么多〃 提交于 2019-12-08 04:55:09
问题 The data is present at the very bottom of the page and is called LDA.scores'. This is a classification task where I performed three supervised machine learning classification techniques on the data-set. All coding is supplied to show how these ROC curves were produced. I apologise for asking a loaded question but I have been trying to solve these issues using different combinations of code for almost two weeks, so if anyone can help me, then thank you. The main issue is the Naive Bayes curve

ROC curve in R using rpart package?

徘徊边缘 提交于 2019-12-07 17:38:42
问题 I split Train data set and Test data set. I used a package rpart for CART (classification tree) in R (only train set). And I want to carry out a ROC analysis using the ROCR package. Variable is `n. use' (response varible... 1=yes, 0=no): > Pred2 = prediction(Pred.cart, Test$n.use) Error in prediction(Pred.cart, Test$n.use) : **Format of predictions is invalid.** This is my code. What is problem? And what is right type ( "class" or "prob" ? library(rpart) train.cart = rpart(n.use~., data=Train

How to compute AUC with ROCR package

喜夏-厌秋 提交于 2019-12-06 22:27:41
问题 I have fitted a SVM model and created the ROC curve with ROCR package. How can I compute the Area Under the Curve (AUC)? set.seed(1) tune.out=tune(svm ,Negative~.-Positive, data=trainSparse, kernel ="radial",ranges=list(cost=c(0.1,1,10,100,1000),gamma=c(0.5,1,2,3,4) )) summary(tune.out) best=tune.out$best.model ##prediction on the test set ypred = predict(best,testSparse, type = "class") table(testSparse$Negative,ypred) ###Roc curve yhat.opt = predict(best,testSparse,decision.values = TRUE)

Plotting a linear discriminant analysis, classification tree and Naive Bayes Curve on a single ROC plot

为君一笑 提交于 2019-12-06 22:17:51
The data is present at the very bottom of the page and is called LDA.scores'. This is a classification task where I performed three supervised machine learning classification techniques on the data-set. All coding is supplied to show how these ROC curves were produced. I apologise for asking a

How to plot a ROC curve for a knn model

痞子三分冷 提交于 2019-12-06 09:29:11
问题 I am using ROCR package and i was wondering how can one plot a ROC curve for knn model in R? Is there any way to plot it all with this package? I don't know how to use the prediction function of ROCR for knn. Here's my example, i am using isolet dataset from UCI repository where i renamed the class attribute as y: cl<-factor(isolet_training$y) knn_isolet<-knn(isolet_training, isolet_testing, cl, k=2, prob=TRUE) Now my question is, what are the arguments to pass to the prediction function of

Using cross validation and AUC-ROC for a logistic regression model in sklearn

亡梦爱人 提交于 2019-12-06 05:17:48
问题 I'm using the sklearn package to build a logistic regression model and then evaluate it. Specifically, I want to do so using cross validation, but can't figure out the right way to do so with the cross_val_score function. According to the documentation and some examples I saw, I need to pass the function the model, the features, the outcome, and a scoring method. However, the AUC doesn't need predictions, it needs probabilities, so it can try different threshold values and calculate the ROC

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