https://github.com/khushi130404/standardize_purchase

Standardized Purchase is a Python program that predicts item purchases based on age and salary, demonstrating the effect of standardization on Logistic Regression and Decision Trees, with visualizations via scatter and KDE plots.
https://github.com/khushi130404/standardize_purchase

descision-tree logistic-regression matplotlib python sklearn standardization

Last synced: 3 months ago
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Standardized Purchase is a Python program that predicts item purchases based on age and salary, demonstrating the effect of standardization on Logistic Regression and Decision Trees, with visualizations via scatter and KDE plots.

• Host: GitHub
• URL: https://github.com/khushi130404/standardize_purchase
• Owner: Khushi130404
• License: mit
• Created: 2024-12-19T05:31:05.000Z (5 months ago)
• Default Branch: main
• Last Pushed: 2025-01-02T11:03:55.000Z (5 months ago)
• Last Synced: 2025-01-02T12:21:00.580Z (5 months ago)
• Topics: descision-tree, logistic-regression, matplotlib, python, sklearn, standardization
• Language: Jupyter Notebook
• Homepage:
• Size: 710 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Standardize_Purchase

Standardized Purchase is a Python program designed to determine if an individual will purchase an item based on their age and salary. It demonstrates the effect of standardization scaling on classification models such as Logistic Regression and Decision Trees. The program visualizes the results using scatter plots and Kernel Density Estimation (KDE) plots.

## Features

- Standardization Scaling: Applies standardization to dataset features to ensure they have a mean of 0 and a standard deviation of 1.

- Logistic Regression: Implements logistic regression for classification tasks.

- Decision Tree: Uses a decision tree classifier to compare performance.

## Visualization:

- Scatter plots to illustrate model decision boundaries.

- KDE plots to analyze data distributions.

## Prerequisites

- numpy

- pandas

- matplotlib

- seaborn

- scikit-learn