逻辑回归与插入符号和glmnet在R

我试图用逻辑回归模型来适合我的数据，使用glmnet（用于套索）和caret（用于k-fold交叉验证）。我尝试了两种不同的语法，但他们都抛出一个错误：逻辑回归与插入符号和glmnet在R

fitControl <- trainControl(method = "repeatedcv", 
         number = 10, 
         repeats = 3, 
         verboseIter = TRUE) 

# with response as a integer (0/1) 
fit_logistic <- train(response ~., 
        data = df_without, 
        method = "glmnet", 
        trControl = fitControl, 
        family = "binomial") 

Error in cut.default(y, breaks, include.lowest = TRUE) : 
invalid number of intervals 

df_without$response <- as.factor(df_without$response) 
# with response as a factor 
fit_logistic <- train(as.matrix(df_without[1:47]), df_without$response, 
       method = "glmnet", 
       trControl = fitControl, 
       family = "binomial") 

Error in lognet(x, is.sparse, ix, jx, y, weights, offset, alpha, nobs, : 
    NA/NaN/Inf in foreign function call (arg 5) 
In addition: Warning message: 
In lognet(x, is.sparse, ix, jx, y, weights, offset, alpha, nobs, : 
    NAs introduced by coercion

我需要我的数据帧转换为矩阵或没有？

我的响应变量是否需要一个因子或只是0/1整数？

带有df_without数据帧的.Rdata文件为here。

sessionInfo()

R version 3.2.0 (2015-04-16) 
Platform: x86_64-apple-darwin13.4.0 (64-bit) 
Running under: OS X 10.10.1 (Yosemite) 

locale: 
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8 

attached base packages: 
[1] parallel splines stats  graphics grDevices utils   datasets methods base  

other attached packages: 
[1] e1071_1.6-4  plyr_1.8.2  gbm_2.1.1  survival_2.38-1  glmnet_2.0-2 foreach_1.4.2 
[7] Matrix_1.2-0 caret_6.0-47 ggplot2_1.0.1 lattice_0.20-31  lubridate_1.3.3 RJDBC_0.2-5  
[13] rJava_0.9-6  DBI_0.3.1  

loaded via a namespace (and not attached): 
[1] Rcpp_0.11.6   compiler_3.2.0  nloptr_1.0.4   class_7.3-12  iterators_1.0.7  
[6] tools_3.2.0   digest_0.6.8  lme4_1.1-7    memoise_0.2.1  nlme_3.1-120  
[11] gtable_0.1.2  mgcv_1.8-6   brglm_0.5-9    SparseM_1.6   proto_0.3-10  
[16] BradleyTerry2_1.0-6 stringr_1.0.0  gtools_3.5.0   grid_3.2.0   nnet_7.3-9   
[21] minqa_1.2.4   reshape2_1.4.1  car_2.0-25    magrittr_1.5  scales_0.2.4  
[26] codetools_0.2-11 MASS_7.3-40   pbkrtest_0.4-2   colorspace_1.2-6 quantreg_5.11  
[31] stringi_0.4-1  munsell_0.4.2

来源

2015-06-20 skunkwerk

的问题是，你有你的数据集的连续变量。 GLMNET需要有二元变量的因子。

如果您运行第一行代码并选择一些非连续变量，您将看到它按预期运行。

来源

2015-06-21 09:11:23 phiver

当然，glmnet和任何其他回归一样，都适用于连续变量。 –

我有同样的问题，我使用函数model.matrix来修复我的分类变量的编码。

尝试此在glmnet X参数：

as.matrix(model.matrix(response ~ .)[, -1])

我除去截距列，因为在glmnet默认的是包括截距。

来源

2016-01-12 15:58:58 felix000

逻辑回归与插入符号和glmnet在R

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