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Logo Cognitive Foundry 3.4.2

by Baz - October 30, 2015, 06:53:03 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 24861 views, 4211 downloads, 4 subscriptions

About: The Cognitive Foundry is a modular Java software library of machine learning components and algorithms designed for research and applications.

Changes:
  • General:
    • Upgraded MTJ to 1.0.3.
  • Common:
    • Added package for hash function computation including Eva, FNV-1a, MD5, Murmur2, Prime, SHA1, SHA2
    • Added callback-based forEach implementations to Vector and InfiniteVector, which can be faster for iterating through some vector types.
    • Optimized DenseVector by removing a layer of indirection.
    • Added method to compute set of percentiles in UnivariateStatisticsUtil and fixed issue with percentile interpolation.
    • Added utility class for enumerating combinations.
    • Adjusted ScalarMap implementation hierarchy.
    • Added method for copying a map to VectorFactory and moved createVectorCapacity up from SparseVectorFactory.
    • Added method for creating square identity matrix to MatrixFactory.
    • Added Random implementation that uses a cached set of values.
  • Learning:
    • Implemented feature hashing.
    • Added factory for random forests.
    • Implemented uniform distribution over integer values.
    • Added Chi-squared similarity.
    • Added KL divergence.
    • Added general conditional probability distribution.
    • Added interfaces for Regression, UnivariateRegression, and MultivariateRegression.
    • Fixed null pointer exception that can happen in K-means with an empty cluster.
    • Fixed name of maxClusters property on AgglomerativeClusterer (was called maxMinDistance).
  • Text:
    • Improvements to LDA Gibbs sampler.

Logo JMLR dlib ml 18.18

by davis685 - October 29, 2015, 01:48:44 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 129003 views, 21313 downloads, 4 subscriptions

About: This project is a C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems.

Changes:

This release has focused on build system improvements, both for the Python API and C++ builds using CMake. This includes adding a setup.py script for installing the dlib Python API as well as a make install target for installing a C++ shared library for non-Python use.


Logo NPD Face Detector Training 1.0

by openpr_nlpr - October 8, 2015, 04:22:36 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1132 views, 228 downloads, 2 subscriptions

About: This MATLAB package provides the Deep Quadratic Tree (DQT) and the Normalized Pixel Difference (NPD) based face detector training method proposed in our PAMI 2015 paper. It is fast, and effective for unconstrained face detection. For more details, please visit http://www.cbsr.ia.ac.cn/users/scliao/projects/npdface/.

Changes:

Initial Announcement on mloss.org.


Logo r-cran-CORElearn 1.47.1

by r-cran-robot - September 3, 2015, 00:00:00 CET [ Project Homepage BibTeX Download ] 9890 views, 2294 downloads, 0 subscriptions

About: Classification, Regression and Feature Evaluation

Changes:

Fetched by r-cran-robot on 2016-01-01 00:00:04.581774


Logo r-cran-Boruta 5.0.0

by r-cran-robot - January 1, 2016, 00:00:04 CET [ Project Homepage BibTeX Download ] 15307 views, 3297 downloads, 2 subscriptions

About: Wrapper Algorithm for All-Relevant Feature Selection

Changes:

Fetched by r-cran-robot on 2016-01-01 00:00:04.263457


Logo Optunity 1.1.1

by claesenm - September 30, 2015, 07:06:17 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5172 views, 1241 downloads, 3 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 Chalearn gesture challenge code by jun wan 2.0

by joewan - September 29, 2015, 08:50:22 CET [ BibTeX BibTeX for corresponding Paper Download ] 4730 views, 1175 downloads, 2 subscriptions

About: This code is provided by Jun Wan. It is used in the Chalearn one-shot learning gesture challenge (round 2). This code includes: bag of features, 3D MoSIFT-based features (i.e. 3D MoSIFT, 3D EMoSIFT and 3D SMoSIFT), and the MFSK feature.

Changes:

Initial Announcement on mloss.org.


Logo SALSA.jl 0.0.5

by jumutc - September 28, 2015, 17:28:56 CET [ Project Homepage BibTeX Download ] 869 views, 159 downloads, 1 subscription

About: SALSA (Software lab for Advanced machine Learning with Stochastic Algorithms) is an implementation of the well-known stochastic algorithms for Machine Learning developed in the high-level technical computing language Julia. The SALSA software package is designed to address challenges in sparse linear modelling, linear and non-linear Support Vector Machines applied to large data samples with user-centric and user-friendly emphasis.

Changes:

Initial Announcement on mloss.org.


Logo KEEL Knowledge Extraction based on Evolutionary Learning 3.0

by keel - September 18, 2015, 12:38:54 CET [ Project Homepage BibTeX Download ] 906 views, 276 downloads, 1 subscription

About: KEEL (Knowledge Extraction based on Evolutionary Learning) is an open source (GPLv3) Java software tool that can be used for a large number of different knowledge data discovery tasks. KEEL provides a simple GUI based on data flow to design experiments with different datasets and computational intelligence algorithms (paying special attention to evolutionary algorithms) in order to assess the behavior of the algorithms. It contains a wide variety of classical knowledge extraction algorithms, preprocessing techniques (training set selection, feature selection, discretization, imputation methods for missing values, among others), computational intelligence based learning algorithms, hybrid models, statistical methodologies for contrasting experiments and so forth. It allows to perform a complete analysis of new computational intelligence proposals in comparison to existing ones. Moreover, KEEL has been designed with a two-fold goal: research and educational. KEEL is also coupled with KEEL-dataset: a webpage that aims at providing to the machine learning researchers a set of benchmarks to analyze the behavior of the learning methods. Concretely, it is possible to find benchmarks already formatted in KEEL format for classification (such as standard, multi instance or imbalanced data), semi-supervised classification, regression, time series and unsupervised learning. Also, a set of low quality data benchmarks is maintained in the repository.

Changes:

Initial Announcement on mloss.org.


Logo WEKA 3.7.13

by mhall - September 11, 2015, 04:55:02 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 53987 views, 8016 downloads, 4 subscriptions

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About: The Weka workbench contains a collection of visualization tools and algorithms for data analysis and predictive modelling, together with graphical user interfaces for easy access to this [...]

Changes:

In core weka:

  • Numerically stable implementation of variance calculation in core Weka classes - thanks to Benjamin Weber
  • Unified expression parsing framework (with compiled expressions) is now employed by filters and tools that use mathematical/logical expressions - thanks to Benjamin Weber
  • Developers can now specify GUI and command-line options for their Weka schemes via a new unified annotation-based mechanism
  • ClassConditionalProbabilities filter - replaces the value of a nominal attribute in a given instance with its probability given each of the possible class values
  • GUI package manager's available list now shows both packages that are not currently installed, and those installed packages for which there is a more recent version available that is compatible with the base version of Weka being used
  • ReplaceWithMissingValue filter - allows values to be randomly (with a user-specified probability) replaced with missing values. Useful for experimenting with methods for imputing missing values
  • WrapperSubsetEval can now use plugin evaluation metrics

In packages:

  • alternatingModelTrees package - alternating trees for regression
  • timeSeriesFilters package, contributed by Benjamin Weber
  • distributedWekaSpark package - wrapper for distributed Weka on Spark
  • wekaPython package - execution of CPython scripts and wrapper classifier/clusterer for Scikit Learn schemes
  • MLRClassifier in RPlugin now provides access to almost all classification and regression learners in MLR 2.4

Showing Items 41-50 of 609 on page 5 of 61: Previous 1 2 3 4 5 6 7 8 9 10 Next Last