About This System

🤖 Machine Learning Model

This system uses a Random Forest Classifier (200 decision trees) trained on 72 years of real Maharashtra Rajya Sabha election data (1952–2024). Each tree votes on the outcome; the final win probability is the average across all trees.

⚡ Recency Weighting

Not all elections are equal — politics changes over time! The model uses exponential decay weighting so that recent elections matter more:

📊 What the Model Looks At (9 Features)

• Party Identity: Encoded party name — model learns each party's historical pattern
• MLA Strength: How many MLAs the party currently holds
• Alliance Strength: Combined MLA count including all coalition partners
• Alliance Majority Flag: Whether the alliance holds ≥145 MLAs — the key RS election trigger
• MLA Share %: Party's share of all 288 Maharashtra seats (normalised)
• Alliance Share %: Alliance's share of all 288 seats (normalised)
• Past Rajya Sabha Wins: Historical RS track record
• Candidate Type: New, Experienced/Incumbent, or Mixed
• Year: Captures political era trends (with recency weighting)

🎯 Model Stats

⚠️ Disclaimer

Predictions are based on historical patterns only. Real elections can be affected by many factors not captured here — current events, campaign strategies, voter sentiment, etc. Use this as an informational tool, not a definitive forecast.