我正在解决一个问题来拟合回归模型并计算我的数据的错误率。我在下面收到一条错误消息：
性能错误（预测（inpPred，inpTruth），测量=metrTmp）： 找不到函数“性能”
这是我的可重现代码
wifiDat <- read.table("wifi_localization.txt",sep="\t")
colnames(wifiDat) <- c("WF1", "WF2", "WF3", "WF4", "WF5", "WF6", "WF7", "RM")
wifiDat$RM <- factor(wifiDat$RM)
dim(wifiDat)
summary(wifiDat)
head(wifiDat)
ggpairs(wifiDat,aes(colour=RM))
glm.fit <- glm(RM~WF1+WF2+WF3+WF4+WF5+WF6+WF7,data=wifiDat,family=binomial)
glmPred <- predict(glm.fit,type="response")>0.5
table(wifiDat[,"RM"],glmPred)
SummPreds <- function(inpPred,inpTruth,inpMetrNms=c("err","acc","sens","spec")) {
retVals <- numeric()
for ( metrTmp in inpMetrNms ) {
retVals[metrTmp] <- performance(prediction(inpPred,inpTruth),measure=metrTmp)@y.values[[1]] [2]
}
retVals
} SummPreds(as.numeric(1+glmPred),as.numeric(wifiDat[,"RM"]))
这是我的示例数据
V1。 V2. V3. V4. V5. V6. V7. V8 -64 -56 -61 -66 -71 -82 -81 1 -68 -57 -61 -65 -71 -85 -85 2 -63 -60 -60 -67 -76 -85 -84 3 -61 -60 -68 -62 -77 -90 -80 4 -63 -65 -60 -63 -77 -81 -87 1 -64 -55 -63 -66 -76 -88 -83 1 -65 -61 -65 -67 -69 -87 -84 2 -61 -63 -58 -66 -74 -87 -82 3 -65 -60 -59 -63 -76 -86 -82 4 -62 -60 -66 -68 -80 -86 -91 1 -67 -61 -62 -67 -77 -83 -91 1 -65 -59 -61 -67 -72 -86 -81 1 -63 -57 -61 -65 -73 -84 -84 1
请问我做错了什么？