Classification with gbm() - errors
gbm, r
Solution
As the error says, your response is not in [0,1]. You can do this instead of creating the factor:
> cancer$class <- (cancer$class -2)/2
> boost.cancer <- gbm(class ~ .-V1, data = cancer, distribution = "bernoulli")
> boost.cancer
gbm(formula = class ~ . - V1, distribution = "bernoulli", data = cancer)
A gradient boosted model with bernoulli loss function.
100 iterations were performed.
There were 9 predictors of which 4 had non-zero influence.
Problem
``` cancer <- read.csv('breast-cancer-wisconsin.data', header = FALSE, na.strings="?") cancer <- cancer[complete.cases(cancer),] names(cancer)[11] <- "class" cancer[, 11] <- factor(cancer[, 11], labels = c("benign", "malignant")) library(gbm) ``` - Data - Data Description Firstly, I remove 'NA' values using complete.cases and make the eleventh column, the "class", as factor. I want to use "class" as the response variable and other columns, except the first one, as predictor variables. On my first attempt, I typed in: ``` boost.cancer <- gbm(class ~ .-V1, data = cancer, distribution = "bernoulli") Error in gbm.fit(x, y, offset = offset, distribution = distribution, w = w, : Bernoulli requires the response to be in {0,1} ``` Then, I use the contrasts of the class instead of class. ``` boost.cancer <- gbm(contrasts(class) ~ .-V1, distribution = "bernoulli", data = cancer) Error in model.frame.default(formula = contrasts(class) ~ . - V1, data = cancer, : variable lengths differ (found for 'V1') ``` How do I correct these errors? I'm sure there is something wrong with my method.