engineer
Unverified ML strategy on Multi by ml4t. BotFinder score 18 out of 100.
Feature engineering, labeling, alternative bars, and leakage-safe datasets for financial ML.
Source: github
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engineer
ml4t-engineer Feature engineering, labeling, alternative bars, and leakage-safe datasets for financial ML. ml4t-engineer provides 120 registry features across 11 categories, path-dependent and fixed-horizon labeling, activity-based bar sampling, and train-only preprocessing. The core interface uses Polars DataFrames. Installation ml4t-engineer supports Python 3.12, 3.13, and 3.14 on Linux, macOS, and Windows. The quick start uses only core dependencies. Optional extras provide TA-Lib validation, DuckDB and PyArrow storage, market calendars, visualization, statistics, and ML tools: TA-Lib requires its native library. The core package does not require an external service, credentials, or special hardware. Python 3.15 is not supported while the active Polars compatibility exception applies. Quick Start computefeatures() returns the input columns with the requested feature columns appended. Use the feature registry to inspect categories and parameters before building larger pipelines. Supported Workflows - Technical, volatility, risk, microstructure, statistical, and ML-oriented features
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