Income Predicting using Random Forest Classifier and Exploratory Data Analysis of the income dataset

[smty2018]

Description

Predicting Income using Random Forest Classifier and Exploratory Data Analysis of the income dataset:

Description:
This project encompasses exploratory data analysis and predictive modelling for income classification using a Random Forest Classifier. The dataset, loaded from a CSV file, contains diverse socio-economic features. It employs advanced visualizations, including a correlation network, to uncover intricate feature relationships. After preprocessing and encoding,A Random Forest Classifier predicts income levels.

EDA Graphs:

Correlation Network

Pairplot:

Stripplot

Box-plot

ViolinPlot

KDE

Correlation Matrix

Model: Random Forest Classifier:

Fixes #2779

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• Bug fix (non-breaking change which fixes an issue)
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• This change requires a documentation update
• Documentation Update

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• [x ] My code follows the style guidelines(Clean Code) of this project
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• [x ] I have created a helpful and easy to understand README.md
• [x ] My documentation follows Template for README.md
• [x ] I have added the project meta data in the PR template.
• [x ] I have created the requirements.txt file if needed.

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