r 计算精度，召回率，准确度，f度量

Posted 2021-05-24

#http://stats.stackexchange.com/questions/37411/calculating-precision-and-recall-in-r
# Pass in data.frame(pred, target)
# Function: evaluation metrics
    ## True positives (TP) - Correctly idd as success
    ## True negatives (TN) - Correctly idd as failure
    ## False positives (FP) - success incorrectly idd as failure
    ## False negatives (FN) - failure incorrectly idd as success
    ## Precision - P = TP/(TP+FP) how many idd actually success/failure
    ## Recall - R = TP/(TP+FN) how many of the successes correctly idd
    ## F-score - F = (2 * P * R)/(P + R) harm mean of precision and recall
prf <- function(predAct){
    ## predAct is two col dataframe of pred,act
    preds = predAct[,1]
    trues = predAct[,2]
    xTab <- table(preds, trues)
    clss <- as.character(sort(unique(preds)))
    r <- matrix(NA, ncol = 7, nrow = 1, 
        dimnames = list(c(),c('Acc',
        paste("P",clss[1],sep='_'), 
        paste("R",clss[1],sep='_'), 
        paste("F",clss[1],sep='_'), 
        paste("P",clss[2],sep='_'), 
        paste("R",clss[2],sep='_'), 
        paste("F",clss[2],sep='_'))))
    r[1,1] <- sum(xTab[1,1],xTab[2,2])/sum(xTab) # Accuracy
    r[1,2] <- xTab[1,1]/sum(xTab[,1]) # Miss Precision
    r[1,3] <- xTab[1,1]/sum(xTab[1,]) # Miss Recall
    r[1,4] <- (2*r[1,2]*r[1,3])/sum(r[1,2],r[1,3]) # Miss F
    r[1,5] <- xTab[2,2]/sum(xTab[,2]) # Hit Precision
    r[1,6] <- xTab[2,2]/sum(xTab[2,]) # Hit Recall
    r[1,7] <- (2*r[1,5]*r[1,6])/sum(r[1,5],r[1,6]) # Hit F
    r}