多类别模型的准确性，精确度和召回率 [英] Accuracy, precision, and recall for multi-class model

问题描述

如何从混淆矩阵中为每个类别计算准确性，精确度和召回?我正在使用嵌入式数据集虹膜；混淆矩阵如下:

How do I calculate accuracy, precision and recall for each class from a confusion matrix? I am using the embedded dataset iris; the confusion matrix is as below:

prediction   setosa versicolor virginica
setosa         29          0         0
versicolor      0         20         2
virginica       0          3        21

我正在使用75个条目作为训练集，而其他用于测试:

I am using 75 entries as the training set and other for testing:

iris.train <- c(sample(1:150, 75)) # have selected 75 randomly

推荐答案

在这个答案中， mat 是您描述的混淆矩阵.

Throughout this answer, mat is the confusion matrix that you describe.

您可以使用以下方法计算和存储准确性:

You can calculate and store accuracy with:

(accuracy <- sum(diag(mat)) / sum(mat))
# [1] 0.9333333

每个类的精度(假设预测在行上，真实结果在列上)可以通过以下方式计算:

Precision for each class (assuming the predictions are on the rows and the true outcomes are on the columns) can be computed with:

(precision <- diag(mat) / rowSums(mat))
#     setosa versicolor  virginica 
#  1.0000000  0.9090909  0.8750000 

如果要获取特定类的精度，可以执行以下操作:

If you wanted to grab the precision for a particular class, you could do:

(precision.versicolor <- precision["versicolor"])
# versicolor 
#  0.9090909 

对于每个班级的回忆(同样假设预测在行上，真实结果在列上)可以使用以下公式计算:

Recall for each class (again assuming the predictions are on the rows and the true outcomes are on the columns) can be calculated with:

recall <- (diag(mat) / colSums(mat))
#     setosa versicolor  virginica 
#  1.0000000  0.8695652  0.9130435 

如果您想召回特定班级，可以执行以下操作:

If you wanted recall for a particular class, you could do something like:

(recall.virginica <- recall["virginica"])
# virginica 
# 0.9130435 

如果相反，您将真实结果作为行，将预测结果作为列，那么您将翻转精度并调用定义.

If instead you had the true outcomes as the rows and the predicted outcomes as the columns, then you would flip the precision and recall definitions.

数据:

(mat = as.matrix(read.table(text="  setosa versicolor virginica
 setosa         29          0         0
 versicolor      0         20         2
 virginica       0          3        21", header=T)))
#            setosa versicolor virginica
# setosa         29          0         0
# versicolor      0         20         2
# virginica       0          3        21

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