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https://github.com/jmrichardson/tuneta
Intelligently optimizes technical indicators and optionally selects the least intercorrelated for use in machine learning models
https://github.com/jmrichardson/tuneta
correlation finance hyperparameter-optimization machine-learning optimize optuna pareto-front stock-market stocks technical-analysis technical-indicators trading trading-systems tune
Last synced: about 2 months ago
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Intelligently optimizes technical indicators and optionally selects the least intercorrelated for use in machine learning models
- Host: GitHub
- URL: https://github.com/jmrichardson/tuneta
- Owner: jmrichardson
- License: mit
- Created: 2021-01-20T01:05:51.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2023-10-13T21:26:28.000Z (11 months ago)
- Last Synced: 2024-05-21T12:17:02.546Z (4 months ago)
- Topics: correlation, finance, hyperparameter-optimization, machine-learning, optimize, optuna, pareto-front, stock-market, stocks, technical-analysis, technical-indicators, trading, trading-systems, tune
- Language: Python
- Homepage:
- Size: 713 KB
- Stars: 382
- Watchers: 13
- Forks: 63
- Open Issues: 5
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Metadata Files:
- Readme: README.md
- License: LICENSE
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- awesome-quant - TuneTA - TuneTA optimizes technical indicators using a distance correlation measure to a user defined target feature such as next day return. (Python / Trading & Backtesting)