パッケージ: python3-mlpy (3.5.0+ds-2)
high-performance Python package for predictive modeling
mlpy provides high level procedures that support, with few lines of code, the design of rich Data Analysis Protocols (DAPs) for preprocessing, clustering, predictive classification and feature selection. Methods are available for feature weighting and ranking, data resampling, error evaluation and experiment landscaping.
mlpy includes: SVM (Support Vector Machine), KNN (K Nearest Neighbor), FDA, SRDA, PDA, DLDA (Fisher, Spectral Regression, Penalized, Diagonal Linear Discriminant Analysis) for classification and feature weighting, I-RELIEF, DWT and FSSun for feature weighting, RFE (Recursive Feature Elimination) and RFS (Recursive Forward Selection) for feature ranking, DWT, UWT, CWT (Discrete, Undecimated, Continuous Wavelet Transform), KNN imputing, DTW (Dynamic Time Warping), Hierarchical Clustering, k-medoids, Resampling Methods, Metric Functions, Canberra indicators.
その他の python3-mlpy 関連パッケージ
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- dep: python3
- 対話式の高レベルオブジェクト指向言語 (デフォルト python3 バージョン)
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- dep: python3-mlpy-lib (>= 3.5.0+ds-2)
- low-level implementations and bindings for mlpy
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- dep: python3-numpy
- Fast array facility to the Python 3 language
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- dep: python3-scipy
- scientific tools for Python 3
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- sug: python3-mvpa
- パッケージは利用できません