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6349363502 of 82199 results
63493.
This package includes the control utility "mini-buildd-tool" along with the "mini_buildd" Python package.
Description
(no translation yet)
Located in Package: python-mini-buildd
63494.
Small boost::python wrapper of parts of the Eigen library
Summary
(no translation yet)
Located in Package: python-minieigen
63495.
Small wrapper for core parts of Eigen, c++ library for linear algebra. It is mainly useful for inspecting c++ code which already uses eigen and boost::python. Supported types are Vectors (2,3,6 and dynamic-sized with integer and floating-point values), Matrices (3x3, 6x6 and dynamic-sized with floating-point values) and Quaternions. Numerous methods are wrapped and the original API of Eigen is followed.
Description
(no translation yet)
Located in Package: python3-minieigen
63496.
binding for Sundown, a markdown parsing library - python 2.x
Summary
(no translation yet)
Located in Package: python-misaka
63497.
Helps to query MK livestatus and return results as dictionary
Summary
(no translation yet)
Located in Package: python-mk-livestatus
63498.
Python MK Livestatus parser ===========================
Description
(no translation yet)
Located in Package: python-mk-livestatus
63499.
Access the data returned from MK Livestatus queries as Python lists or dictionaries. It does this by sending queries to the MK Livestatus UNIX socket and parses the returned rows. Read/write permission to the UNIX socket are required.
Description
(no translation yet)
Located in Package: python-mk-livestatus
63500.
high-performance Python package for predictive modeling
Summary
Paquet Python à haute performance pour la modélisation prédictive
Translated by Anne017
Reviewed by gisele perreault
Located in Package: python3-mlpy
63501.
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.
Description
(no translation yet)
Located in Package: python-mlpy
63502.
documention and examples for mlpy
Summary
Documention et exemples pour mlpy
Translated and reviewed by Pierre Slamich
Located in Package: python-mlpy-doc
6349363502 of 82199 results

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