错误：nrow（x）== n使用列车在插入中时不为TRUE [英] Error: nrow(x) == n is not TRUE when using Train in Caret

问题描述

我有一个训练集，看起来像

I have a training set that looks like

Name       Day         Area         X    Y    Month Night
ATTACK    Monday   LA           -122.41 37.78   8      0
VEHICLE  Saturday  CHICAGO      -1.67    3.15   2      0
MOUSE     Monday   TAIPEI       -12.5    3.1    9      1

名称是结果/因变量。我将名称，区域和 Day 转换为因素，我不知道我是否应该是月和 Night ，它只占整数值1-12和0-1。

Name is the outcome/dependent variable. I converted Name, Area and Day into factors, but I wasn't sure if I was supposed to for Month and Night, which only take on integer values 1-12 and 0-1, respectively.

然后将数据转换为矩阵

ynn <- model.matrix(~Name , data = trainDF)
mnn <- model.matrix(~ Day+Area +X + Y + Month + Night, data = trainDF)

然后我设置调整参数

nnTrControl=trainControl(method = "repeatedcv",number = 3,repeats=5,verboseIter = TRUE, returnData = FALSE, returnResamp = "all", classProbs = TRUE, summaryFunction = multiClassSummary,allowParallel = TRUE)
nnGrid = expand.grid(.size=c(1,4,7),.decay=c(0,0.001,0.1))
model <- train(y=ynn, x=mnn, method='nnet',linout=TRUE, trace = FALSE, trControl = nnTrControl,metric="logLoss", tuneGrid=nnGrid)

但是，我得到错误错误：nrow（x）== n不是真的为模型< -train

如果我使用 xgboost 而不是 nnet

任何人都知道什么是ca使用这个？

Anyone know whats causing this?

推荐答案

y 应该是一个数字或因子矢量，包含每个样本的结果，而不是矩阵。使用

y should be a numeric or factor vector containing the outcome for each sample, not a matrix. Using

train(y = make.names(trainDF$Name), ...)

帮助，其中 make.names 修改值，使其成为有效的变量名。

helps, where make.names modifies values so that they could be valid variable names.

这篇关于错误：nrow（x）== n使用列车在插入中时不为TRUE的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！