Prediction Using Simple Linear Regression

Implementation of simple linear regression to predict delivery time.

Objective

Is to predict the delivery time using sorting time.

Overview

Used perticular libreries to perform EDA,plotting and to get data information . Used Linear Regression model to predict the delivery time.

Methodology

1.Preprocessing and EDA:

Performed EDA to get more informative features about the given data set and got the below insights.

• No null values in dataset.
• No outliers in dataset.
• delivery time is having 82.5% correlation with sorting time.
• maximum occurence of sorting time is 7.
• max delivery time is 29, min delivery time is 8, average delivery time is 17
• max sorting time is 10, min sorting time is 2, average sorting time is 6. max sorting time count is 7.

2.Model Building and Model Validation:

Model used here is simple Linear Regression. Model validation done by using r2_score and root mean square error and got

• model intercept_ is 6.6 and coef_ is 1.60
• model r2_score is 57% and RMSE is 2.33

Insights:

• In above project we have dataset of delivery time and sorting time.
• It is observed that delivery time and sorting time is strongly correlate with each other.
• max delivery time is 29, min delivery time is 8, average delivery time is 17
• max sorting time is 10, min sorting time is 2, average sorting time is 6. max sorting time count is 7.
• Then built simple linear regression machine learning model to predit delivery time based on sorting time.
• model coefficient of determination is 0.57, so model is good fit.