我有一个包含 60 行(=样本)和 20228 列的数据框“数据”,其中第一列是我的目标变量(有序因子:0 或 1),其他列是我的特征(=数字)。我想在循环中使用 mRMRe 进行特征选择,对应于我执行 3 次的 5 交叉验证。我每次都会选择 25 个特征。这是我的代码有问题的部分:
library(caret)
library(mRMRe)
data <- read.csv("home/RNA_seq.csv", row.names=1, sep=";", stringsAsFactors=FALSE)
data <- data.frame(t(data))
data[,1] <- factor(data[,1])
data[,1] <- ordered(data[,1], levels = c("0", "1"))
features_select <- list()
r <- 5 # 5-cross-validation
t <- 3 # 5-cross-validation done 3 times
for (j in 1:t){
for (i in 1:r){
#5-cross-validation
train.index <- createFolds(factor(data$Response), k = 5, list = TRUE, returnTrain = TRUE)
datatrain <- data[train.index[[i]],]
datatest <- data[-train.index[[i]],]
#Feature selection
data.mrmre.train <- mRMR.data(data=datatrain)
res.fs.mrmr <- mRMR.classic(data=data.mrmre.train, target_indices=1, feature_count=25)
selected.features.mrmre <- mRMRe::solutions(res.fs.mrmr)
features_select[[((j-1)*r+i)]] <- res.fs.mrmr@feature_names[unlist(selected.features.mrmre)]
print(features_select[[((j-1)*r+i)]])
print(res.fs.mrmr)
}
}
我的问题是,有时 mRMRe 选择名为“Response”(=“数据”的第 1 列)的目标变量。举例来说:
features_select :
[[1]]
[1] "AC137800.2" "AC007387.1" "AC079354.1" "AC145138.1" "RNA5SP370"
[6] "RNA5SP219" "AL022324.1" "AC023449.1" "AP000873.1" "AC020612.2"
[11] "RNA5SP473" "AC092810.1" "IGKV1D.37" "SST" "AC093331.1"
[16] "TRAJ34" "AC107983.1" "RPL39P" "HSBP1P1" "TRBJ1.6"
[21] "PHGR1" "RNA5SP435" "RNA5SP301" "AC005255.1" "KRT127P"
[[2]]
[1] "AC073869.8" "Response" "Response" "Response" "Response" "Response"
[7] "Response" "Response" "Response" "Response" "Response" "Response"
[13] "Response" "Response" "Response" "Response" "Response" "Response"
[19] "Response" "Response" "Response" "Response" "Response" "Response"
[25] "Response"
这是函数 mRMR.classic() 在第一种情况和第二种情况(=坏情况)下的输出:
[[1]]
Formal class 'mRMRe.Filter' [package "mRMRe"] with 8 slots
..@ filters :List of 1
.. ..$ 1: int [1:25, 1] 18837 18781 15503 15526 17437 20028 18924 17133 17024 16104 ...
..@ scores :List of 1
.. ..$ 1: num [1:25, 1] 0.817 0.819 0.817 0.817 0.817 ...
..@ mi_matrix : num [1:20228, 1:20228] NA -0.3786 -0.1536 -0.0929 -0.0964 ...
.. ..- attr(*, "dimnames")=List of 2
.. .. ..$ : chr [1:20228] "Response" "TMSB15B" "MATR3" "HSPA14" ...
.. .. ..$ : chr [1:20228] "Response" "TMSB15B" "MATR3" "HSPA14" ...
..@ causality_list:List of 1
.. ..$ 1: num [1:20228] NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN ...
..@ sample_names : chr [1:48] "Pt1_28" "Pt2_28" "Pt4_28" "Pt5_28" ...
..@ feature_names : chr [1:20228] "Response" "TMSB15B" "MATR3" "HSPA14" ...
..@ target_indices: int 1
..@ levels : int [1:25] 1 1 1 1 1 1 1 1 1 1 ...
[[2]]
Formal class 'mRMRe.Filter' [package "mRMRe"] with 8 slots
..@ filters :List of 1
.. ..$ 1: int [1:25, 1] 1 1 1 1 1 1 1 1 1 1 ...
..@ scores :List of 1
.. ..$ 1: num [1:25, 1] 0 0 0 0 0 0 0 0 0 0 ...
..@ mi_matrix : num [1:20228, 1:20228] NA -0.518 -0.246 -0.211 -0.204 ...
.. ..- attr(*, "dimnames")=List of 2
.. .. ..$ : chr [1:20228] "Response" "TMSB15B" "MATR3" "HSPA14" ...
.. .. ..$ : chr [1:20228] "Response" "TMSB15B" "MATR3" "HSPA14" ...
..@ causality_list:List of 1
.. ..$ 1: num [1:20228] NA NaN NaN NaN NaN NaN NaN NaN NaN NaN ...
..@ sample_names : chr [1:48] "Pt1_28" "Pt2_28" "Pt4_28" "Pt5_28" ...
..@ feature_names : chr [1:20228] "Response" "TMSB15B" "MATR3" "HSPA14" ...
..@ target_indices: int 1
..@ levels : int [1:25] 1 1 1 1 1 1 1 1 1 1 ...
对于相同的 i 和 j 值进入循环时,不会每次都会出现这种情况。您知道问题出在哪里吗?
提前谢谢您!
最佳答案
我收到了 mRMRe 包作者的回复。解决方案是使用“strata”参数来指示mRMR.data()
中的我的目标变量(=有序因子)。功能。所以,我必须改变:
data.mrmre.train <- mRMR.data(data=datatrain)
至:
data.mrmre.train <- mRMR.data(data=datatrain[,-1], strata=datatrain[,1])
.
关于r - 使用mRMRe进行特征选择: my categorical target variable is sometimes selected,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/59953732/