{"repo":"izikeros/trend_classifier","free":true,"listed":false,"github":"https://github.com/izikeros/trend_classifier","clone":"git clone https://github.com/izikeros/trend_classifier.git","description":"Library for automated signal segmentation, trend classification and analysis.","language":"Jupyter Notebook","stars":34,"topics":["timeseries-segmentation","trend-analysis","trend-detection","algorithmic-trading","algotrading","trading-bot"],"license":"MIT","category":"trading","readme_excerpt":"trend classifier Automated signal segmentation, trend classification and analysis. Documentation Tutorials API Reference Quick Start Installation With optional dependencies: Features - Multiple detection algorithms : - sliding window - Original algorithm, interpretable, good for most cases - bottom up - Merge-based, control exact segment count - pelt - Optimal segmentation via ruptures library - Rich segment information : slope, offset, volatility, trend consistency - DataFrame export : seg.segments.to dataframe() - Visualization : plot segments() , plot segment() - Configurable : Fine-tune sensitivity with alpha , beta , window size Example with Stock Data Using Different Detectors Segment Properties Each segment contains: Property Description ---------- ------------- start , stop Index range slope Trend direction and steepness std Volatility (after detrending) reason for new segment Why segment boundary was placed Documentation Full documentation with tutorials and API reference: https://izikeros.github.io/trend classifier/ License MIT © Krystian Safjan","default_branch":null,"files":null,"tree":[],"storefront":"/r/izikeros","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/izikeros/trend_classifier/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}