CODEWITHSUNDEEP
rr-caretrpart
redeemefy
redeemefy

Reputation: 4849

Error training with caret method rpart R

I'm having and error while trying to train a dataset with the caret package. The error is the following... Error in train.default(x, y, weights = w, ...) : Stopping. I also have warnings() which all of them are the same because I'm creating an object for the tuneGrid with the following code...grid <- expand.grid(cp = seq(0, 0.05, 0.005)). This code is creating a data.frame with 11 rows that correspond to the 11 warnings I'm having. Here is the warning... In eval(expr, envir, enclos) : model fit failed for Fold01: cp=0 Error in[.data.frame(m, labs) : undefined columns selected. Looks like the cp doesn't have anything. I can go to my environment and see the grid object and all 11 rows. I have search stackoverflow and I found similar questions but since these functions have so many ways to tweak them, I haven't found a question that fix my problem. Here is my code...

require(rpart)
require(rattle)
require(rpart.plot)
require(caret)


setwd('~/Documents/Lipscomb/predictive_analytics/class4/')
data <- read.csv(file = 'data.csv',
                 head = FALSE)

data <- subset(data, select = -V1)

colnames(data) <-  c('diagnostic', 'm.radius', 'm.texture', 'm. perimeter', 'm.area', 'm.smoothness', 'm.compactness', 'm.concavity', 'm.concave.points', 'm.symmetry', 'm.fractal.dimension',
                     'se.radius', 'se.texture', 'se. perimeter', 'se.area', 'se.smoothness', 'se.copactness', 'se.concavity', 'se.concave.points', 'se.symmetry', 'se.fractal.dimension',
                     'w.radius', 'w.texture', 'w. perimeter', 'w.area', 'w.smoothness', 'w.copactness', 'w.concavity', 'w.concave.points', 'w.symmetry', 'w.fractal.dimension')

str(data)

set.seed(7)
sample.train <- sample(1:nrow(data), nrow(data) * .8)
sample.test <- setdiff(1:nrow(data), sample.train)


data.train <- data[sample.train, ]
data.test <- subset(data[sample.test, ], select = -diagnostic)

rpart.tree <- rpart(diagnostic ~ ., data = data.train)
out <- predict(rpart.tree, data.test, type = 'class')
table(out, data[sample.test, ]$diagnostic)

fancyRpartPlot(rpart.tree)

temp <- rpart.control(xval = 10, minbucket = 2, minsplit = 4, cp = 0)
dfit <- rpart(diagnostic ~ ., data = data.train, control = temp)
fancyRpartPlot(dfit)

fit.control <- trainControl(method = 'cv', number = 10)
grid <- expand.grid(cp = seq(0, 0.05, 0.005))
trained.tree <- train(diagnostic ~ ., method = 'rpart', data = data.train, 
                      metric = 'Accuracy', maximize = TRUE,
                      trControl = fit.control, tuneGrid = grid)

Upvotes: 0

Views: 1537

Answers (1)

redeemefy
redeemefy

Reputation: 4849

I have found a solution to this problem. I changed the way I was naming my colnames. For some reason, the original code for naming colnames was causing error utilizing the train function. This code fixed the problem.

colnames(data) <-  c('diagnostic', 'radius', 'texture', 'perimeter', 'area', 'smoothness', 'compactness', 'concavity', 'concavePoints', 'symmetry', 'fractalDimension',
                     'SeRadius', 'SeTexture', 'SePerimeter', 'SeArea', 'SeSmoothness', 'SeCopactness', 'SeConcavity', 'SeConcavePoints', 'SeSymmetry', 'SeFractalDimension',
                     'Wradius', 'Wtexture', 'Wperimeter', 'Warea', 'Wsmoothness', 'Wcopactness', 'Wconcavity', 'WconcavePoints', 'Wsymmetry', 'WfractalDimension')

Upvotes: 1

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