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Logo Operator Discretization Library 0.6

by jonasadl - December 19, 2017, 15:24:08 CET [ Project Homepage BibTeX Download ] 6909 views, 1860 downloads, 0 subscriptions

About: Operator Discretization Library (ODL) is a Python library that enables research in inverse problems on realistic or real data.

Changes:

Initial Announcement on mloss.org.


Logo Optunity 1.1.1

by claesenm - September 30, 2015, 07:06:17 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 32163 views, 7624 downloads, 0 subscriptions

About: Optunity is a library containing various optimizers for hyperparameter tuning. Hyperparameter tuning is a recurrent problem in many machine learning tasks, both supervised and unsupervised.This package provides several distinct approaches to solve such problems including some helpful facilities such as cross-validation and a plethora of score functions.

Changes:

This minor release has the same feature set as Optunity 1.1.0, but incorporates several bug fixes, mostly related to the specification of structured search spaces.


Logo OptWok 0.3.1

by ong - May 2, 2013, 10:46:11 CET [ Project Homepage BibTeX Download ] 30699 views, 6479 downloads, 0 subscriptions

About: A collection of python code to perform research in optimization. The aim is to provide reusable components that can be quickly applied to machine learning problems. Used in: - Ellipsoidal multiple instance learning - difference of convex functions algorithms for sparse classfication - Contextual bandits upper confidence bound algorithm (using GP) - learning output kernels, that is kernels between the labels of a classifier.

Changes:
  • minor bugfix

Logo opusminer 0.1-0

by opusminer - February 23, 2017, 01:01:18 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 8441 views, 1726 downloads, 0 subscriptions

About: The new R package opusminer provides an R interface to the OPUS Miner algorithm (implemented in C++) for finding the key associations in transaction data efficiently, in the form of self-sufficient itemsets, using either leverage or lift.

Changes:

Initial Announcement on mloss.org.


Logo Orange 2.6

by janez - February 14, 2013, 18:15:08 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 36984 views, 7848 downloads, 0 subscriptions

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About: Orange is a component-based machine learning and data mining software. It includes a friendly yet powerful and flexible graphical user interface for visual programming. For more advanced use(r)s, [...]

Changes:

The core of the system (except the GUI) no longer includes any GPL code and can be licensed under the terms of BSD upon request. The graphical part remains under GPL.

Changed the BibTeX reference to the paper recently published in JMLR MLOSS.


Logo Ordinal Choquistic Regression 1.00

by AliFall - January 30, 2014, 15:42:34 CET [ BibTeX BibTeX for corresponding Paper Download ] 6955 views, 1988 downloads, 0 subscriptions

About: "Ordinal Choquistic Regression" model using the maximum likelihood

Changes:

Initial Announcement on mloss.org.


Logo Output Kernel Learning 2.0

by posaune - March 22, 2012, 11:34:58 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 19773 views, 3662 downloads, 0 subscriptions

About: A Matlab script for learning vector-valued functions and kernels on the output space.

Changes:

Added code for learning low-rank output kernels.


Logo OXlearn 1.0

by gwestermann - January 11, 2010, 11:48:26 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 12421 views, 2698 downloads, 0 subscriptions

About: OXlearn is a free neural network simulation software that enables you to build, train, test and analyse connectionist neural network models. Because OXlearn is implemented as a Matlab toolbox you can run it on all operation systems (Windows, Linux, MAC, etc.), and there is a compiled version for XP.

Changes:

Initial Announcement on mloss.org.


Logo PALMA: mRNA to Genome Alignments using Large Margin Algorithms 0.3.7

by gxr - November 26, 2007, 21:14:57 CET [ Project Homepage BibTeX Download ] 10942 views, 3170 downloads, 0 subscriptions

About: PALMA computes the optimal spliced alignment of a mRNA sequence to a genomic sequence. The main python script takes two FASTA files containing the target (e.g. a DNA sequence, part of the genome) [...]

Changes:

Initial Announcement on mloss.org.


Logo parcor Regularized estimation of partial correlation matrices 0.1

by nkraemer - May 5, 2009, 16:49:47 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 11259 views, 2482 downloads, 0 subscriptions

About: The package estimates the matrix of partial correlations based on different regularized regression methods: lasso, adaptive lasso, PLS, and Ridge Regression.

Changes:

Initial Announcement on mloss.org.


Logo Partition Comparison 1.0

by andres - April 21, 2012, 03:26:47 CET [ Project Homepage BibTeX Download ] 8151 views, 2682 downloads, 0 subscriptions

About: Fast C++ implementation of the variation of information (Meila 2003) and Rand index (Rand 1971) with MATLAB mex files

Changes:

Initial Announcement on mloss.org.


Logo Pattern 2.4

by tomdesmedt - August 31, 2012, 02:26:01 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 24568 views, 7530 downloads, 0 subscriptions

About: "Pattern" is a web mining module for Python. It bundles tools for data retrieval, text analysis, clustering and classification, and data visualization.

Changes:
  • Small bug fixes in overall + performance improvements.
  • Module pattern.web: updated to the new Bing API (Bing API has is paid service now).
  • Module pattern.en: now includes Norvig's spell checking algorithm.
  • Module pattern.de: new German tagger/chunker, courtesy of Schneider & Volk (1998) who kindly agreed to release their work in Pattern under BSD.
  • Module pattern.search: the search syntax now includes { } syntax to define match groups.
  • Module pattern.vector: fast implementation of information gain for feature selection.
  • Module pattern.graph: now includes a toy semantic network of commonsense (see examples).
  • Module canvas.js: image pixel effects & editor now supports live editing

Logo Pattern Recognition for Neuroimaging Toolbox v1.1

by chrisp - September 16, 2013, 23:19:56 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 11225 views, 2827 downloads, 0 subscriptions

About: PRoNTo is freely available software and aims to facilitate the interaction between the neuroimaging and machine learning communities. The toolbox is based on pattern recognition techniques for the analysis of neuroimaging data. PRoNTo supports the analysis of all image modalities as long as they are NIfTI format files. However, only the following modalites have been tested for version 1.1: sMRI, fMRI, PET, FA (fractional anisotropy) and Beta (GLM coefficients) images.

Changes:

Initial Announcement on mloss.org.


Logo pattern recognition tool 1.0

by openpr_nlpr - January 19, 2016, 03:54:11 CET [ Project Homepage BibTeX Download ] 7571 views, 2029 downloads, 0 subscriptions

About: a tool for marking samples in images for database building, also including algorithm of LBP,HOG,and classifiers of SVM (six kernels), adaboost,BP and convolutional networks, extreme learning machine.

Changes:

Initial Announcement on mloss.org.


Logo pboost 1.0

by nowozin - November 13, 2007, 08:48:28 CET [ Project Homepage BibTeX Download ] 9424 views, 2616 downloads, 0 subscriptions

About: The pboost toolbox is a set of command line programs and a Matlab wrapper for mining frequent subsequences and sequence classification. For our purposes, a sequence is defined an ordered sequence of [...]

Changes:

Initial Announcement on mloss.org.


Logo JMLR pebl Python Environment for Bayesian Learning 1.0.1

by abhik - March 5, 2009, 00:05:28 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 43995 views, 5516 downloads, 0 subscriptions

About: Pebl is a python library and command line application for learning the structure of a Bayesian network given prior knowledge and observations.

Changes:

Updated version to 1.0.1


Logo peewit 0.10

by lorenz - May 7, 2014, 16:04:18 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 74059 views, 15344 downloads, 0 subscriptions

About: peewit provides services for programming, running and result examination of machine learning experiments. It does not include any ML algorithms, has no GUI, and presumes certain uniformity of the experimental layout. But it does not make assumptions on the type of task under study. The current version-number is 0.10.

Changes:

v-cube with side-cubes


Logo Penalized Partial Least Squares Regression 1.03

by nkraemer - May 5, 2009, 19:53:20 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 22939 views, 3902 downloads, 0 subscriptions

About: This package contains functions to estimate linear and nonlinear regression methods with Penalized Partial Least Squares.

Changes:
  • fixed several bugs
  • drastic speed-up of computation time

Logo Perspective 3 Points Solver 1.0.0

by openpr_nlpr - December 2, 2011, 05:31:04 CET [ Project Homepage BibTeX Download ] 6607 views, 1921 downloads, 0 subscriptions

About: This is a implementation of the classic P3P(Perspective 3-Points) algorithm problem solution in the Ransac paper "M. A. Fischler, R. C. Bolles. Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography. Comm. of the ACM, Vol 24, pp 381-395, 1981.". The algorithm gives the four probable solutions of the P3P problem in about 0.1ms, and can be used as input of the consequent RANSAC step. The codes needs the numerics library VNL which is a part of the widely used computer vision library VXL. One can download & install it from http://vxl.sourceforge.net/.

Changes:

Initial Announcement on mloss.org.


Logo pGBRT, Parallel Gradient Boosted Regression Trees 0.9

by swtyree - September 16, 2011, 22:15:46 CET [ Project Homepage BibTeX Download ] 21590 views, 3396 downloads, 0 subscriptions

About: Learns gradient boosted regression tree ensembles in parallel on shared memory or cluster systems

Changes:

Initial Announcement on mloss.org.


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