分类分析--选择预测效果最好的解

分类分析--选择预测效果最好的解

预测准确性度量

下面给出计算这几个统计量的函数：

评估二分类准确性：

performance <- function(table, n=2){

 if(!all(dim(table) == c(2,2)))

stop("Must be a 2 x 2 table")

（1）第一步：得到频数

tn = table[1,1]

fp = table[1,2]

fn = table[2,1]

tp = table[2,2]

（2）第二步：计算统计量

sensitivity = tp/(tp+fn)

 specificity = tn/(tn+fp)

 ppp = tp/(tp+fp)

 npp = tn/(tn+fn)

 hitrate = (tp+tn)/(tp+tn+fp+fn)

（3）第三步：输出结果

result <- paste("Sensitivity = ", round(sensitivity, n) ,

 "\nSpecificity = ", round(specificity, n),

 "\nPositive Predictive Value = ", round(ppp, n),

 "\nNegative Predictive Value = ", round(npp, n),

 "\nAccuracy = ", round(hitrate, n), "\n", sep="")

 cat(result)

}

以下代码清单将performance()函数用于上述提到的五个分类器：

逻辑回归