Binary package “python3-mlpy” in ubuntu jammy
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.
Source package
Published versions
- python3-mlpy 3.5.0+ds-1.3build2 in amd64 (Proposed)
- python3-mlpy 3.5.0+ds-1.3build2 in amd64 (Release)
- python3-mlpy 3.5.0+ds-1.3build2 in arm64 (Proposed)
- python3-mlpy 3.5.0+ds-1.3build2 in arm64 (Release)
- python3-mlpy 3.5.0+ds-1.3build2 in armhf (Proposed)
- python3-mlpy 3.5.0+ds-1.3build2 in armhf (Release)
- python3-mlpy 3.5.0+ds-1.3build2 in i386 (Proposed)
- python3-mlpy 3.5.0+ds-1.3build2 in i386 (Release)
- python3-mlpy 3.5.0+ds-1.3build2 in ppc64el (Proposed)
- python3-mlpy 3.5.0+ds-1.3build2 in ppc64el (Release)
- python3-mlpy 3.5.0+ds-1.3build2 in riscv64 (Proposed)
- python3-mlpy 3.5.0+ds-1.3build2 in riscv64 (Release)
- python3-mlpy 3.5.0+ds-1.3build2 in s390x (Proposed)
- python3-mlpy 3.5.0+ds-1.3build2 in s390x (Release)