README.md

metadata

license: mit
language:
  - en
metrics:
  - accuracy
pipeline_tag: tabular-classification
library_name: sklearn
tags:
  - scikit-learn
  - finance
  - cryptocurrency
  - sentiment-analysis

Model Description

This is a supervised machine learning model trained to forecast short-term cryptocurrency trend bias (Bullish, Bearish, or Neutral). It is the core prediction engine for the CryptoRadar full-stack platform.

• Model Type: Scikit-Learn Classifier
• Primary Use Case: Predicting directional market momentum based on technical and sentiment data.

Input Features

The model evaluates a 10-dimensional feature vector:

• volume, dxy_index, price_change_pct, rsi, volatility, dist_from_sma
• sentiment_coin, sentiment_trend_coin, sentiment_btc, sentiment_trend_btc

Limitations

This model is for educational and portfolio purposes only. Cryptocurrency markets are highly volatile, and this model should not be used for actual financial trading.