Historical Data Analysis

Algorithms Used:

• LSTMs (Long Short-Term Memory Networks): Models historical price and volume trends to predict future performance.

• k-Means (Clustering): Groups tokens with similar performance metrics, aiding in comparative analysis.

• XGBoost (Predictive Modeling): Predicts token growth potential based on historical data like market cap, transaction volume, and price stability.

Benefits:

• Identifies tokens with consistent growth and adoption.

• Flags tokens with volatile or declining trends.

• Provides actionable insights into market performance and potential risks.