tuneta
Indicator optimizer
Automates optimization of technical indicators for machine learning models in finance
Intelligently optimizes technical indicators and optionally selects the least intercorrelated for use in machine learning models
421 stars
13 watching
69 forks
Language: Python
last commit: over 1 year ago
Linked from 1 awesome list
correlationfinancehyperparameter-optimizationmachine-learningoptimizeoptunapareto-frontstock-marketstockstechnical-analysistechnical-indicatorstradingtrading-systemstune
wilsonfreitas/awesome-quantRelated projects:
| Repository | Description | Stars |
|---|---|---|
 jiangoforit/yellowfin_pytorch | An optimizer that automatically tunes momentum and learning rate using local quadratic approximation. | 287 |
 syne-tune/syne-tune | A tool for large-scale and asynchronous hyperparameter optimization in machine learning | 393 |
 liyanghart/hyperparameter-optimization-of-machine-learning-algorithms | Provides tools and techniques for tuning hyperparameters in machine learning models to improve performance. | 1,283 |
 nicholas-leonard/drmad | A toolbox for efficient hyperparameter tuning in deep learning using Bayesian optimization and automatic differentiation | 23 |
 rodrigo-arenas/sklearn-genetic-opt | Automated hyperparameter tuning and feature selection using evolutionary algorithms. | 316 |
 jo-cho/technical_analysis_and_feature_engineering | Analyzing and applying machine learning techniques to financial markets using feature engineering and technical indicators. | 127 |
 jrmeier/fast-trade | Enables quick analysis and backtesting of trading strategies using technical indicators and chart data | 377 |
 huntermcgushion/hyperparameter_hunter | Automates hyperparameter optimization and result saving across machine learning algorithms | 706 |
 microsoft/archai | Automates the search for optimal neural network configurations in deep learning applications | 468 |
 kirthevasank/nasbot | An implementation of Neural Architecture Search with Bayesian Optimization and Optimal Transport | 133 |
 robertmartin8/machinelearningstocks | A Python project applying machine learning to predict stock price movements based on historical data and fundamental analysis. | 1,781 |
 lge-arc-advancedai/auptimizer | Automates model building and deployment process by optimizing hyperparameters and compressing models for edge computing. | 200 |
 autonomio/talos | A tool for automating hyperparameter experiments for machine learning models using TensorFlow and Keras | 1,626 |
 jjakimoto/dqn | Reinforcement learning-based algorithm for optimizing stock trading and portfolio management | 182 |
 vivekpa/aialpha | This project trains machine learning models to predict stock returns using various algorithms and techniques. | 1,745 |