Explain how to implement Multiple Linear regression in R

299 Asked by ranjan_6399 in Data Science , Asked on Jan 15, 2020

# Multiple Linear Regression

# Importing the dataset

dataset = read.csv('50_Startups.csv')

# Encoding categorical data

dataset$State = factor(dataset$State,

levels = c('New York', 'California', 'Florida'),

labels = c(1, 2, 3))

# Splitting the dataset into the Training set and Test set

# install.packages('caTools')

library(caTools)

set.seed(123)

split = sample.split(dataset$Profit, SplitRatio = 0.8)

training_set = subset(dataset, split == TRUE)

test_set = subset(dataset, split == FALSE)

# Feature Scaling

# training_set = scale(training_set)

# test_set = scale(test_set)

# Fitting Multiple Linear Regression to the Training set

regressor = lm(formula = Profit ~ .,

data = training_set)

# Predicting the Test set results

y_pred = predict(regressor, newdata = test_set)

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