arXiv:1803.08118
공식 코드 · Papers with Code
Seglearn: A Python Package for Learning Sequences and Time Series
원문 초록
Seglearn is an open-source python package for machine learning time series or sequences using a sliding window segmentation approach. The implementation provides a flexible pipeline for tackling classification, regression, and forecasting problems with multivariate sequence and contextual data. This package is compatible with scikit-learn and is listed under scikit-learn Related Projects. The package depends on numpy, scipy, and scikit-learn. Seglearn is distributed under the BSD 3-Clause License. Documentation includes a detailed API description, user guide, and examples. Unit tests provide a high degree of code coverage.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
A Combination Method for Android Malware Detection Based on Control Flow Graphs and Machine Learning Algorithms
Support Vector Machines with Time Series Distance Kernels for Action Classification
A Review of the Long Horizon Forecasting Problem in Time Series Analysis
The interplay of robustness and generalization in quantum machine learning
A Better Alternative to Piecewise Linear Time Series Segmentation
Process mining-driven modeling and simulation to enhance fault diagnosis in cyber-physical systems
토론
이 논문과 연결된 포럼 글이 아직 없습니다.