https://github.com/waterflow80/inusrance-prediction-model

In in this project we'll try to create different machine learning supervised models for pedicting whether a given house should consider apply for insurance. The data preprocessing and visualization will be included in this project.
https://github.com/waterflow80/inusrance-prediction-model

Last synced: 9 days ago
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In in this project we'll try to create different machine learning supervised models for pedicting whether a given house should consider apply for insurance. The data preprocessing and visualization will be included in this project.

• Host: GitHub
• URL: https://github.com/waterflow80/inusrance-prediction-model
• Owner: waterflow80
• Created: 2024-01-01T11:25:35.000Z (11 months ago)
• Default Branch: main
• Last Pushed: 2024-08-01T16:00:25.000Z (4 months ago)
• Last Synced: 2024-08-01T17:58:26.075Z (4 months ago)
• Language: Jupyter Notebook
• Size: 373 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Inusrance Prediction Model - ML Classification Problem

In in this project we tried to create different machine learning supervised models for pedicting whether an owner of a given house should consider applying for insurance. The data preprocessing and visualization will be included in this project.

The machine learning techniques/models used are: **Decision Tree Classifier**, **Logistic Regression**, **Random Forest Classifier**, **SVM Classifier**, and **MLP Classifier**. 

## The Code

- The `main.ipynb` is the main entry point for the project.

- Other files contain useful code for formatting, normalizing, and preprocessing of the data.

## Description and Analysis

TODO