Metadata-Version: 2.4
Name: bcpipeline
Version: 0.1.0
Summary: Binary Classification Pipeline with feature engineering and ensemble methods
Home-page: https://github.com/mazyad-alrashidi/binary-classification-pipeline
Author: Mazyad Alrashidi
Author-email: mzydhaif11@gmail.com
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Requires-Dist: numpy>=1.21
Requires-Dist: pandas>=1.3
Requires-Dist: scikit-learn>=1.0
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary


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# 🚀 Binary Classification Pipeline

### End-to-end ML pipeline with feature engineering & ensemble methods

![Python](https://img.shields.io/badge/Python-3.10%2B-blue?style=for-the-badge&logo=python&logoColor=white)
![Scikit-learn](https://img.shields.io/badge/Scikit--learn-latest-orange?style=for-the-badge&logo=scikitlearn&logoColor=white)
![License](https://img.shields.io/badge/License-MIT-emerald?style=for-the-badge)
![Version](https://img.shields.io/badge/Version-0.1.0-gold?style=for-the-badge)

<br>

[![Install](https://img.shields.io/badge/pip%20install-bcpipeline-%23FFD700?style=for-the-badge&logo=pypi&logoColor=black)](#installation)
[![Stars](https://img.shields.io/github/stars/mazyad-alrashidi/binary-classification-pipeline?style=for-the-badge&label=⭐%20Star&color=%23FF69B4)](https://github.com/mazyad-alrashidi/binary-classification-pipeline)

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> *"One line to install. One class to classify."*

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## 📦 Installation

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```bash
pip install git+https://github.com/mazyad-alrashidi/binary-classification-pipeline.git
```

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## ⚡ Usage

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| Step | Code | Result |
|------|------|--------|
| ① Import | `from bcpipeline import BinaryClassifier` | ✅ Ready |
| ② Initialize | `clf = BinaryClassifier()` | ✅ Configured |
| ③ Train | `clf.fit(X, y)` | 🏆 Best model selected |
| ④ Predict | `clf.predict(X_new)` | 🎯 Predictions ready |
| ⑤ Evaluate | `clf.evaluate()` | 📊 Full metrics |

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## 💎 Features

<table>
<tr>
<td width="40">🔧</td>
<td><strong>Feature Engineering</strong></td>
<td align="right"><code>Interaction · Ratio · Squared</code></td>
</tr>
<tr>
<td>🤖</td>
<td><strong>Multi-Model Comparison</strong></td>
<td align="right"><code>LR · SVM · RF · GBM</code></td>
</tr>
<tr>
<td>⚙️</td>
<td><strong>Hyperparameter Tuning</strong></td>
<td align="right"><code>Grid Search + 5-fold CV</code></td>
</tr>
<tr>
<td>🎯</td>
<td><strong>Ensemble Voting</strong></td>
<td align="right"><code>Soft voting top 3 models</code></td>
</tr>
<tr>
<td>📈</td>
<td><strong>Threshold Optimization</strong></td>
<td align="right"><code>Optimal decision boundary</code></td>
</tr>
</table>

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## 📊 Performance

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| Model | Accuracy | Status |
|-------|----------|--------|
| Logistic Regression | ~95% | 🟡 Good |
| SVM (RBF) | ~90% | 🟡 Moderate |
| Random Forest | ~100% | 🟢 Excellent |
| Gradient Boosting | ~100% | 🟢 Excellent |
| **Ensemble** | **100%** | 🌟 Outstanding |

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## 🛠️ Tech Stack

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| Category | Tools |
|----------|-------|
| Language | <img src="https://img.shields.io/badge/Python-3776AB?style=flat-square&logo=python&logoColor=white" /> |
| ML Framework | <img src="https://img.shields.io/badge/Scikit--learn-F7931E?style=flat-square&logo=scikitlearn&logoColor=white" /> |
| Data Processing | <img src="https://img.shields.io/badge/Pandas-150458?style=flat-square&logo=pandas&logoColor=white" /> |
| Visualization | <img src="https://img.shields.io/badge/Matplotlib-11557C?style=flat-square&logo=matplotlib&logoColor=white" /> |

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### Made with ❤️ by [Mazyad Alrashidi](https://github.com/mazyad-alrashidi)

🇸🇦 Riyadh, Saudi Arabia

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⭐ **If you find this useful, give it a star!**

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