20 projects found that use java as the programming language.
Showing Items 1-20 of 79 on page 1 of 4: 1 2 3 4 Next

Logo KeLP 1.1.0

by kelpadmin - May 26, 2015, 15:47:03 CET [ Project Homepage BibTeX Download ] 498 views, 102 downloads, 2 subscriptions

About: Kernel-based Learning Platform (KeLP) is Java framework that supports the implementation of kernel-based learning algorithms, as well as an agile definition of kernel functions over generic data representation, e.g. vectorial data or discrete structures. The framework has been designed to decouple kernel functions and learning algorithms, through the definition of specific interfaces. Once a new kernel function has been implemented, it can be automatically adopted in all the available kernel-machine algorithms. KeLP includes different Online and Batch Learning algorithms for Classification, Regression and Clustering, as well as several Kernel functions, ranging from vector-based to structural kernels. It allows to build complex kernel machine based systems, leveraging on JSON/XML interfaces to instantiate classifiers without writing a single line of code.

Changes:

Many fixes and new functionalities are included in this version. Among them, an efficient and full version of the Smoothed Partial Tree Kernel is for the first time available to the public.

Check out this new version from our repositories. Soon we will upload new versions of the documentation pages, while API Javadoc is already available.

Your suggestions will be very precious for us, so download and try KeLP 1.1.0!

New Representations: - SequenceRepresentation

New Kernels: - SubSetTreeKernel - SmoothedPartialTreeKernel - CompositionallySmoothedPartialTreeKernel - SequenceKernel

New LearningAlgorithms: - LibLinearRegression - BudgetedPassiveAggressive


Logo Cognitive Foundry 3.4.1

by Baz - May 13, 2015, 06:55:24 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 19574 views, 3207 downloads, 3 subscriptions

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

Changes:
  • General:
    • Updated MTJ to version 1.0.2 and netlib-java to 1.1.2.
    • Updated XStream to version 1.4.8.
  • Common:
    • Fixed issue in VectorUnionIterator.
  • Learning:
    • Added Alternating Least Squares (ALS) Factorization Machine training implementation.
    • Fixed performance issue in Factorization Machine where linear component was not making use of sparsity.
    • Added utility function to sigmoid unit.

About: FAST is an implementation of Hidden Markov Models with Features. It allows features to modify both emissions and transition probabilities.

Changes:

Initial Announcement on mloss.org.


Logo BLOG 0.9.1

by jxwuyi - April 27, 2015, 06:52:05 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 470 views, 90 downloads, 3 subscriptions

About: Bayesian Logic (BLOG) is a probabilistic modeling language. It is designed for representing relations and uncertainties among real world objects.

Changes:

Initial Announcement on mloss.org.


Logo python weka wrapper 0.3.1

by fracpete - April 23, 2015, 00:06:57 CET [ Project Homepage BibTeX Download ] 11910 views, 2501 downloads, 3 subscriptions

About: A thin Python wrapper that uses the javabridge Python library to communicate with a Java Virtual Machine executing Weka API calls.

Changes:
  • added "get_tags" class method to "Tags" class for easier instantiation of Tag arrays
  • added "find" method to "Tags" class to locate "Tag" object that matches the string
  • fixed "getitem" and "setitem" methods of the "Tags" class
  • added "GridSearch" meta-classifier with convenience properties to module "weka.classifiers"
  • added "SetupGenerator" and various parameter classes to "weka.core.classes"
  • added "MultiSearch" meta-classifier with convenience properties to module "weka.classifiers"
  • added "quote"/"unquote" and "backquote"/"unbackquote" methods to "weka.core.classes" module
  • added "main" method to "weka.core.classes" for operations on options: join, split, code
  • added support for option handling to "weka.core.classes" module

Logo java machine learning platform 1.0

by openpr_nlpr - April 2, 2015, 09:02:14 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 644 views, 101 downloads, 2 subscriptions

About: Jmlp is a java platform for both of the machine learning experiments and application. I have tested it on the window platform. But it should be applicable in the linux platform due to the cross-platform of Java language. It contains the classical classification algorithm (Discrete AdaBoost.MH, Real AdaBoost.MH, SVM, KNN, MCE,MLP,NB) and feature reduction(KPCA,PCA,Whiten) etc.

Changes:

Initial Announcement on mloss.org.


Logo Hivemall 0.3

by myui - March 13, 2015, 17:08:22 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5581 views, 894 downloads, 3 subscriptions

About: Hivemall is a scalable machine learning library running on Hive/Hadoop.

Changes:
  • Supported Matrix Factorization
  • Added a support for TF-IDF computation
  • Supported AdaGrad/AdaDelta
  • Supported AdaGradRDA classification
  • Added normalization scheme

Logo ADAMS 0.4.8

by fracpete - March 4, 2015, 00:54:04 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 10893 views, 2379 downloads, 3 subscriptions

About: The Advanced Data mining And Machine learning System (ADAMS) is a novel, flexible workflow engine aimed at quickly building and maintaining real-world, complex knowledge workflows.

Changes:
  • 13 new actors
  • 1 new conversion
  • new module adams-access: for accessing MS Access databases (read/write)
  • adams-heatmap module overhaul
  • adams-imaging: barcode (QRCode etc) encoding/decoding, multi-image operations (and, or, xor)
  • Flow editor gets a "quick edit" tab
  • MEKA upgraded to 1.7.5
  • Weka filter "Scale" (unsupervised/instance) allows you to scale the values of a row eg to interval 0 to 1
  • SimplePlot sink is a "dumbed down" version of the SequencePlotter with only basic options -- enough to create good looking plots quickly
  • Upper/LowerCase conversion take the locale into account now
  • added print support for PDFs
  • fixed sluggish behavior in Flow editor (open/save/undo)
  • TryCatch correctly flushes token now
  • spreadsheet column range/index sometimes failed in conjunction with variables
  • fixed memory leak in Weka Explorer plugins FixedClassifierErrorPlot, ThresholdCurve
  • WekaExcel upgraded to 1.0.5 (no longer omits last row in sheets)
  • WhileLoop did not react to changes in variables once looping, ie conditions couldn't make use of variables
  • ImageProcessor now works again with the improved ImageFileChooser dialog
  • PreviewBrowser displays arrays in a more meaningful way
  • WekaFileReader didn't output empty datasets in DATASET mode
  • obtaining subsets from Notes objects only resulted in first element being retrieved

Logo JMLR Mulan 1.5.0

by lefman - February 23, 2015, 21:19:05 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 17194 views, 6661 downloads, 2 subscriptions

About: Mulan is an open-source Java library for learning from multi-label datasets. Multi-label datasets consist of training examples of a target function that has multiple binary target variables. This means that each item of a multi-label dataset can be a member of multiple categories or annotated by many labels (classes). This is actually the nature of many real world problems such as semantic annotation of images and video, web page categorization, direct marketing, functional genomics and music categorization into genres and emotions.

Changes:

Learners

  • MLCSSP.java: Added the MLCSSP algorithm (from ICML 2013)
  • Enhancements of multi-target regression capabilities
  • Improved CLUS support
  • Added pairwise classifier and pairwise transformation

Measures/Evaluation

  • Providing training data in the Evaluator is unnecessary in the case of specific measures.
  • Examples with missing ground truth are not skipped for measures that handle missing values.
  • Added logistics and squared error losses and measures

Bug fixes

  • IndexOutOfBounds in calculation of MiAP and GMiAP
  • Bug fix in Rcut.java
  • When in rank/score mode the meta-data contained additional unecessary attributes. (Newton Spolaor)

API changes

  • Upgrade to Java 7
  • Upgrade to Weka 3.7.10

Miscalleneous

  • Small changes and improvements in the wrapper classes for the CLUS library
  • ENTCS13FeatureSelection.java (new experiment)
  • Enumeration is now used for specifying the type of meta-data. (Newton Spolaor)

Logo JMLR DLLearner 1.0

by Jens - February 13, 2015, 11:39:46 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 16262 views, 4067 downloads, 6 subscriptions

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About: The DL-Learner framework contains several algorithms for supervised concept learning in Description Logics (DLs) and OWL.

Changes:

See http://dl-learner.org/development/changelog/.


About: Learns dynamic network changes across conditions and visualize the results in Cytoscape.

Changes:

Initial Announcement on mloss.org.


Logo Hub Miner 1.1

by nenadtomasev - January 22, 2015, 16:33:51 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1635 views, 297 downloads, 2 subscriptions

About: Hubness-aware Machine Learning for High-dimensional Data

Changes:
  • BibTex support for all algorithm implementations, making all of them easy to reference (via algref package).

  • Two more hubness-aware approaches (meta-metric-learning and feature construction)

  • An implementation of Hit-Miss networks for analysis.

  • Several minor bug fixes.

  • The following instance selection methods were added: HMScore, Carving, Iterative Case Filtering, ENRBF.

  • The following clustering quality indexes were added: Folkes-Mallows, Calinski-Harabasz, PBM, G+, Tau, Point-Biserial, Hubert's statistic, McClain-Rao, C-root-k.

  • Some more experimental scripts have been included.

  • Extensions in the estimation of hubness risk.

  • Alias and weighted reservoir methods for weight-proportional random selection.


Logo JEMLA 1.0

by bathaeian - January 4, 2015, 08:34:49 CET [ Project Homepage BibTeX Download ] 634 views, 177 downloads, 3 subscriptions

About: Java package for calculating Entropy for Machine Learning Applications. It has implemented several methods of handling missing values. So it can be used as a lab for examining missing values.

Changes:

Discretizing numerical values is added to calculate mode of values and fractional replacement of missing ones. class diagram is on the web http://profs.basu.ac.ir/bathaeian/free_space/jemla.rar


Logo WEKA 3.7.12

by mhall - December 17, 2014, 03:04:17 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 45705 views, 6781 downloads, 3 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:

  • GUIChooser now has a plugin exension point that allows implementations of GUIChooser.GUIChooserMenuPlugin to appear as entries in either the Tools or Visualization menus
  • SubsetByExpression filter now has support for regexp matching
  • weka.classifiers.IterativeClassifierOptimizer - a classifier that can efficiently optimize the number of iterations for a base classifier that implements IterativeClassifier
  • Speedup for LogitBoost in the two class case
  • weka.filters.supervised.instance.ClassBalancer - a simple filter to balance the weight of classes
  • New class hierarchy for stopwords algorithms. Includes new methods to read custom stopwords from a file and apply multiple stopwords algorithms
  • Ability to turn off capabilities checking in Weka algorithms. Improves runtime for ensemble methods that create a lot of simple base classifiers
  • Memory savings in weka.core.Attribute
  • Improvements in runtime for SimpleKMeans and EM
  • weka.estimators.UnivariateMixtureEstimator - new mixture estimator

In packages:

  • New discriminantAnalysis package. Provides an implementation of Fisher's linear discriminant analysis
  • Quartile estimators, correlation matrix heat map and k-means++ clustering in distributed Weka
  • Support for default settings for GridSearch via a properties file
  • Improvements in scripting with addition of the offical Groovy console (kfGroovy package) from the Groovy project and TigerJython (new tigerjython package) as the Jython console via the GUIChooser
  • Support for the latest version of MLR in the RPlugin package
  • EAR4 package contributed by Vahid Jalali
  • StudentFilters package contributed by Chris Gearhart
  • graphgram package contributed by Johannes Schneider

Logo JMLR JKernelMachines 2.5

by dpicard - December 11, 2014, 17:51:42 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 17624 views, 4148 downloads, 4 subscriptions

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About: machine learning library in java for easy development of new kernels

Changes:

Version 2.5

  • New active learning algorithms
  • Better threading management
  • New multiclass SVM algorithm based on SDCA
  • Handle class balancing in cross-validation
  • Optional support of EJML switch to version 0.26
  • Various bugfixes and improvements

Logo ABACOC Adaptive Ball Cover for Classification 1.0

by kikot - July 14, 2014, 16:27:03 CET [ BibTeX BibTeX for corresponding Paper Download ] 1392 views, 388 downloads, 3 subscriptions

About: Online Action Recognition via Nonparametric Incremental Learning. Java and Matlab code already available. A Python version and the Java source code will be released soon.

Changes:

Initial release of the library, future changes will be advertised shortly.


Logo Encog Machine Learning Framework 3.2

by jeffheaton - July 5, 2014, 23:47:06 CET [ Project Homepage BibTeX Download ] 3939 views, 1169 downloads, 1 subscription

About: Encog is a Machine Learning framework for Java, C#, Javascript and C/C++ that supports SVM's, Genetic Programming, Bayesian Networks, Hidden Markov Models and other algorithms.

Changes:

Changes for Encog 3.2:

Issue #53: Fix Out Of Range Bug In BasicMLSequenceSet. Issue #52: Unhandled exception in Encog.Util.File.ResourceLoader.CreateStream (ResourceLoader.cs) Issue #50: Concurrency bugs in PruneIncremental Issue #48: Unit Tests Failing - TestHessian Issue #46: Couple of small fixes - Temporal DataSet and SCG training Issue #45: Fixed EndMinutesStrategy to correctly evaluate ShouldStop after the specified number of minutes have elapsed. Issue #44: Encog.ML.Data.Basic.BasicMLDataPairCentroid.Add() & .Remove() Issue #43: Unit Tests Failing - Matrix not full rank Issue #42: Nuget - NuSpec Issue #36: Load Examples easier


Logo Java deep neural networks with GPU 0.2.0-alpha

by hok - May 10, 2014, 14:22:30 CET [ Project Homepage BibTeX Download ] 2031 views, 459 downloads, 2 subscriptions

About: GPU-accelerated java deep neural networks

Changes:

Initial Announcement on mloss.org.


Logo PredictionIO 0.7.0

by simonc - April 29, 2014, 20:59:57 CET [ Project Homepage BibTeX Download ] 7725 views, 1600 downloads, 2 subscriptions

About: Open Source Machine Learning Server

Changes:
  • Single machine version for small-to-medium scale deployments
  • Integrated GraphChi (disk-based large-scale graph computation) and algorithms: ALS, CCD++, SGD, CLiMF
  • Improved runtime for training and offline evaluation
  • Bug fixes

See release notes - https://predictionio.atlassian.net/secure/ReleaseNote.jspa?projectId=10000&version=11801


Logo JMLR MOA Massive Online Analysis Nov-13

by abifet - April 4, 2014, 03:50:20 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 13316 views, 5198 downloads, 1 subscription

About: Massive Online Analysis (MOA) is a real time analytic tool for data streams. It is a software environment for implementing algorithms and running experiments for online learning from evolving data streams. MOA includes a collection of offline and online methods as well as tools for evaluation. In particular, it implements boosting, bagging, and Hoeffding Trees, all with and without Naive Bayes classifiers at the leaves. MOA supports bi-directional interaction with WEKA, the Waikato Environment for Knowledge Analysis, and it is released under the GNU GPL license.

Changes:

New version November 2013


Showing Items 1-20 of 79 on page 1 of 4: 1 2 3 4 Next