Linear Regression : Linear Regressoin is the most basic and popular algorithm of machine learning. It is supervised machine learning algorithm which is predicted output is real values/continuous. Or, Relationship between input/independent variables and single output/dependent variable. We will get linear regression image look like : -
Objective : To make a simple linear regression model operating on one variable from scratch using statistical formulas
Simple Linear Regression A linear line relationship between one input/independent variable(X) and one output/dependent variable(y).
y = mX + b Where, y is dependent/target variable; X is input/independent variable; m is slop of regression line; b is y-intercept.
Approach : The model is built in the following steps
Data Wrangling
Data Cleaning : Missing Values
Visualisation : UniVariate
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Histograms
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Scatter Plot
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Boxplot Parameter Functions :
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Mean and Variance
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Co-Variance
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Coefficients
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Splitting Test Data Model Building and Predictions
RMSE Function building and calculation