Multiple Linear Regression

Multiple Linear Regression is one of the important regression algorithms which models the linear relationship between a single dependent continuous variable and more than one independent variable.

Problem Description:

We have a dataset of 50 start-up companies. This dataset contains five main information: R&D Spend, Administration Spend, Marketing Spend, State, and Profit for a financial year. Our goal is to create a model that can easily determine which company has a maximum profit, and which is the most affecting factor for the profit of a company.

Since we need to find the Profit, so it is the dependent variable, and the other four variables are independent variables. Below are the main steps of deploying the MLR model:

Data Pre-processing Steps Fitting the MLR model to the training set Predicting the result of the test set

Result : The r2 score tells that our model is 77% accurate with the training dataset and 62% accurate with the test dataset.