https://github.com/earthinversion/xgboost_classify_regress

https://github.com/earthinversion/xgboost_classify_regress

Last synced: 14 days ago
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• Host: GitHub
• URL: https://github.com/earthinversion/xgboost_classify_regress
• Owner: earthinversion
• Created: 2024-11-07T02:38:23.000Z (3 months ago)
• Default Branch: main
• Last Pushed: 2024-11-07T02:39:53.000Z (3 months ago)
• Last Synced: 2024-11-07T03:28:20.534Z (3 months ago)
• Language: Jupyter Notebook
• Size: 0 Bytes
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# XGBoost Prediction and Visualization

This repository provides utilities for training, saving, and loading XGBoost models for classification and regression tasks, including data visualization using SHAP (SHapley Additive exPlanations) values. The project includes Jupyter notebooks demonstrating classification on CSV data and the Iris dataset, as well as regression on the California Housing dataset.

## Installation

```bash

conda env create -f environment.yml

conda activate xgboost_training

```

```bash

conda activate xgboost_training

```

## Dependencies

1. XGBoost

1. SHAP (for explainability)

1. Matplotlib (for plotting)

1. Scikit-Learn (for datasets and metrics)

## Troubleshooting

- for osx-arm64

```bash

conda install numpy pandas scipy scikit-learn matplotlib joblib xgboost

```

- for osx-64

```bash

conda install numpy=1.19.2 pandas=1.0.1 scipy=1.6.1 scikit-learn=0.24.0 matplotlib=3.1.3 joblib=0.15.1 xgboost=1.3.1

```