计算R中的AUC(GAM)

时间:2014-06-09 08:05:21

标签: graph r

我使用以下脚本来计算R中的AUC:

library(mgcv)
library(ROCR)
library(AUC)

data1=read.table("d:\\2005.txt", header=T)
GAM<-gam(tuna ~ s(chla)+s(sst)+s(ssha)+s(eke), family=binomial, data=data1)

gampred<- predict(GAM, type="response")

rp <- prediction(gampred, data1$tuna) 

auc <- performance( rp, "auc")@y.values[[1]]
auc

roc <- performance( rp, "tpr", "fpr")
plot( roc )

但是当我运行脚本时,结果是:

rp <- prediction(gampred, data1$tuna) 
Error in prediction(gampred, data1$tuna) : 
  Format of predictions is invalid.

auc <- performance( rp, "auc")@y.values[[1]]
Error in performance(rp, "auc") : object 'rp' not found

auc
function (x, min = 0, max = 1) 
{
    if (any(class(x) == "roc")) {
        if (min != 0 || max != 1) {
            x$fpr <- x$fpr[x$cutoffs >= min & x$cutoffs <= max]
            x$tpr <- x$tpr[x$cutoffs >= min & x$cutoffs <= max]
        }
        ans <- 0
        for (i in 2:length(x$fpr)) {
            ans <- ans + 0.5 * abs(x$fpr[i] - x$fpr[i - 1]) * 
                (x$tpr[i] + x$tpr[i - 1])
        }
    }
    else if (any(class(x) %in% c("accuracy", "sensitivity", "specificity"))) {
        if (min != 0 || max != 1) {
            x$cutoffs <- x$cutoffs[x$cutoffs >= min & x$cutoffs <= 
                max]
            x$measure <- x$measure[x$cutoffs >= min & x$cutoffs <= 
                max]
        }
        ans <- 0
        for (i in 2:(length(x$cutoffs))) {
            ans <- ans + 0.5 * abs(x$cutoffs[i - 1] - x$cutoffs[i]) * 
                (x$measure[i] + x$measure[i - 1])
        }
    }
    return(as.numeric(ans))
}
<bytecode: 0x03012f10>
<environment: namespace:AUC>

roc <- performance( rp, "tpr", "fpr")
Error in performance(rp, "tpr", "fpr") : object 'rp' not found

plot( roc )
Error in levels(labels) : argument "labels" is missing, with no default**

有人可以帮我解决这个问题吗? 提前谢谢。

数据:

structure(list(x.y.chla.sst.ssha.eke.tuna = structure(c(3L, 
2L, 1L, 6L, 5L, 4L, 9L, 8L, 7L, 12L, 11L, 10L, 17L, 16L, 15L, 
14L, 13L, 23L, 22L, 21L, 20L, 19L, 18L, 29L, 28L, 27L, 26L, 25L, 
24L, 34L, 33L, 32L, 31L, 30L, 39L, 38L, 37L, 36L, 35L, 44L, 43L, 
42L, 41L, 40L, 49L, 48L, 47L, 46L, 45L, 54L, 53L, 52L, 51L, 50L, 
57L, 56L, 55L, 60L, 59L, 58L, 63L, 62L, 61L, 66L, 65L, 64L, 69L, 
68L, 67L, 72L, 71L, 70L, 75L, 74L, 73L, 76L, 79L, 78L, 77L, 82L, 
81L, 80L, 85L, 84L, 83L, 88L, 87L, 86L, 91L, 90L, 89L, 94L, 93L, 
92L, 97L, 96L, 95L, 98L, 101L, 100L), .Label = c("140.01178,44.666668,0.21406905,19.939999,6.931947586,213.8725429,87", 
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"143.82654,45.072071,0.4959102,17.92,1.729482292,20.55258129,97"
), class = "factor")), .Names = "x.y.chla.sst.ssha.eke.tuna", row.names = c(NA, 
100L), class = "data.frame")

1 个答案:

答案 0 :(得分:0)

您的data1数据框已经搞乱了。看看str()给你的是什么:

> str(data1)
'data.frame':   100 obs. of  1 variable:
 $ x.y.chla.sst.ssha.eke.tuna: Factor w/ 311 levels "140.01178,44.666668,0.21406905,19.939999,6.931947586,213.8725429,87",..: 3 2 1 6 5 4 9 8 7 12 ...

当你实际上是一个包含单列的数据框时,你可能会认为这是一个带有numericcolumns的数据框。你似乎没有使用正确的'sep'参数就使用了read.table。列名全部组合在一起,值被捆绑在一起作为单个因子串。真糟糕!

最好是回到开始并重做read.table努力。我想可以解析单列的名称,然后在发送因子列的as.character()结果上使用read.table,但这似乎是巴洛克式的。

编辑评论:我也认为大多数人选择AUC工具真的不明白它提供什么。它似乎比它应得的使用频率更高。