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mfmakahiya/data prep.r

Created July 30, 2019 07:07
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data prep.r
library(Matrix)
library(glmnet)
library(pROC)
library(caret)
# Import dataset
data1 = read.csv(file = "./data/input/breast-cancer.csv")
data1$diagnosis<-ifelse(data1$diagnosis=='M', 1,0)
data2 = data.matrix(data1)
Matrix(data2, sparse = TRUE)
set.seed(6789)
# Split the data to train and test
split = sample(nrow(data1), floor(0.7*nrow(data1)))
train = data1[split,]
test = data1[-split,]
train_sparse = sparse.model.matrix(~., train[,3:32])
test_sparse = sparse.model.matrix(~., test[,3:32])
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