在 Mushroom 数据集上调用值为 1 的 c50 代码

Question

我在使用 Mushroom 数据集处理 C5.0 时遇到错误。我已经分解了目标 class 并且没有缺失值。

f <-file("https://archive.ics.uci.edu/ml/machine-learning-databases/mushroom/agaricus-lepiota.data", open="r")
data <- read.table(f, sep=",", header=F)
str(data)

给予

'data.frame':   8124 obs. of  23 variables:
$ V1 : Factor w/ 2 levels "e","p": 2 1 1 2 1 1 1 1 2 1 ...
$ V2 : Factor w/ 6 levels "b","c","f","k",..: 6 6 1 6 6 6 1 1 6 1 ...
$ V3 : Factor w/ 4 levels "f","g","s","y": 3 3 3 4 3 4 3 4 4 3 ...
$ V4 : Factor w/ 10 levels "b","c","e","g",..: 5 10 9 9 4 10 9 9 9 10 ...
$ V5 : Factor w/ 2 levels "f","t": 2 2 2 2 1 2 2 2 2 2 ...
$ V6 : Factor w/ 9 levels "a","c","f","l",..: 7 1 4 7 6 1 1 4 7 1 ...
$ V7 : Factor w/ 2 levels "a","f": 2 2 2 2 2 2 2 2 2 2 ...
$ V8 : Factor w/ 2 levels "c","w": 1 1 1 1 2 1 1 1 1 1 ...
$ V9 : Factor w/ 2 levels "b","n": 2 1 1 2 1 1 1 1 2 1 ...
$ V10: Factor w/ 12 levels "b","e","g","h",..: 5 5 6 6 5 6 3 6 8 3 ...
$ V11: Factor w/ 2 levels "e","t": 1 1 1 1 2 1 1 1 1 1 ...
$ V12: Factor w/ 5 levels "?","b","c","e",..: 4 3 3 4 4 3 3 3 4 3 ...
$ V13: Factor w/ 4 levels "f","k","s","y": 3 3 3 3 3 3 3 3 3 3 ...
$ V14: Factor w/ 4 levels "f","k","s","y": 3 3 3 3 3 3 3 3 3 3 ...
$ V15: Factor w/ 9 levels "b","c","e","g",..: 8 8 8 8 8 8 8 8 8 8 ...
$ V16: Factor w/ 9 levels "b","c","e","g",..: 8 8 8 8 8 8 8 8 8 8 ...
$ V17: Factor w/ 1 level "p": 1 1 1 1 1 1 1 1 1 1 ...
$ V18: Factor w/ 4 levels "n","o","w","y": 3 3 3 3 3 3 3 3 3 3 ...
$ V19: Factor w/ 3 levels "n","o","t": 2 2 2 2 2 2 2 2 2 2 ...
$ V20: Factor w/ 5 levels "e","f","l","n",..: 5 5 5 5 1 5 5 5 5 5 ...
$ V21: Factor w/ 9 levels "b","h","k","n",..: 3 4 4 3 4 3 3 4 3 3 ...
$ V22: Factor w/ 6 levels "a","c","n","s",..: 4 3 3 4 1 3 3 4 5 4 ...
$ V23: Factor w/ 7 levels "d","g","l","m",..: 6 2 4 6 2 2 4 4 2 4 ...

当我运行

C5.model <- C5.0(data[1:4000,-1],data[1:4000,1],trials = 3)

给予

c50 code called exit with value 1

我不知道如何找到这个。对调试的任何想法表示赞赏

Edit1：错误相同，但解决方案不同。注意：当我更改数据集时，它正在工作。

Answer 1

f <-file("https://archive.ics.uci.edu/ml/machine-learning-databases/mushroom/agaricus-lepiota.data", open="r")
data <- read.table(f, sep=",", header=F)
str(data)

pacman::p_load(C50)
C5.model <- C5.0(data[1:10000,c(2:16,18:23)],data[1:10000,1],trials = 3,na.action = na.pass)

第 17 列是导致此问题的原因，因为它没有识别变异。

在 Mushroom 数据集上调用值为 1 的 c50 代码

c50 code called exit with value 1 on Mushroom Data set

r

machine-learning

decision-tree