machinelearning


# This R script will run on our backend. You can write arbitrary code here!

# Many standard libraries are already installed, such as randomForest
library(randomForest)

# The train and test data is stored in the ../input directory
train <- read.csv("../input/train.csv")
test  <- read.csv("../input/test.csv")

# We can inspect the train data. The results of this are printed in the log tab below
summary(train)

# Here we will plot the passenger survival by class
train$Survived <- factor(train$Survived, levels=c(1,0))
levels(train$Survived) <- c("Survived", "Died")
train$Pclass <- as.factor(train$Pclass)
levels(train$Pclass) <- c("1st Class", "2nd Class", "3rd Class")

png("1_survival_by_class.png", width=800, height=600)
mosaicplot(train$Pclass ~ train$Survived, main="Passenger Survival by Class",
           color=c("#8dd3c7", "#fb8072"), shade=FALSE,  xlab="", ylab="",
           off=c(0), cex.axis=1.4)
dev.off()
                

This script has been released under the Apache 2.0 open source license.




Source: machinelearning

Via: Google Alert for ML

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