Search Results for "hidden markov java"

UnBBayes is a probabilistic network framework written in Java. It has both a GUI and an API with inference, sampling, learning and evaluation. It supports Bayesian networks, influence diagrams, MSBN, OOBN, HBN, MEBN/PR-OWL, PRM, structure, parameter and incremental learning. Please, visit our wiki (https://sourceforge.net/p/unbbayes/wiki/Home/) for more information. Check out the license section (https://sourceforge.net/p/unbbayes/wiki/License/) for our licensing policy.

Visual Figaro is an integrated environment to develop component libraries for the dependability modeling tool KB3 used by EDF (http://www.edf.fr/recherche/codes-de-calcul/kb3). KB3 is based on the FIGARO reliability modeling language, suitable for describing CTMC (continuous time Markov chains), DES (discrete event simulation) models, and for automatic generation of fault trees. FIGARO is objet oriented, close to natural language and enables building libraries of reusable components...

BoostMultiDex is a specialized Android-library created by ByteDance to address a long-standing performance and user-experience problem on older Android devices (specifically Android 4.x and below, i.e. SDK < 21), where loading multiple dex files after installation or upgrade can lead to extremely long “black-screen” freeze times during first startup. Instead of relying on the standard Android MultiDex mechanism, BoostMultiDex reworks the loading strategy by tapping into hidden Dalvik VM...

The KReator project is a collection of software systems, tools, algorithms and data structures for logic-based knowledge representation. Currently, it includes the software systems KReator and MECore and the library Log4KR: - KReator is an integrated development environment (IDE) for relational probabilistic knowledge representation languages such as Bayesian Logic Programs (BLPs), Markov Logic Networks (MLNs), Relational Maximum Entropy (RME), First-Order Probabilistic...

The software annotates text with 41 broad semantic categories (Wordnet supersenses) for both nouns and verbs; i.e., it performs both sense disambiguation and named-entity recognition. The tagger implements a discriminatively-trained Hidden Markov Model.

This project provides an implementation of duration high-order hidden Markov model (DHO-HMM) in Java. It is compactible with JDK 5 & 6. It was used in the author's research on speech recognition of Mandarin digits. There are some Chinese words in this project and I am afraid that I don't have enough time to translate to English recently.

The JaCHMM - the Java Conditioned Hidden Markov Model library - is a complete implementation of a CHMM in Java ready to use either on command line or as a module. The JaCHMM is licenced under the BSD licence. It gives an implementation of the Viterbi, Forward-Backward, Baum-Welch and K-Means algorithms, all adapted for the CHMM. JaCHMM is based on the JaHMM and also designed to achieve reasonable performance without making the code unreadable.

JProGraM (PRObabilistic GRAphical Models in Java) is a statistical machine learning library. It supports statistical modeling and data analysis along three main directions: (1) probabilistic graphical models (Bayesian networks, Markov random fields, dependency networks, hybrid random fields); (2) parametric, semiparametric, and nonparametric density estimation (Gaussian models, nonparanormal estimators, Parzen windows, Nadaraya-Watson estimator); (3) generative models for random networks (small-world, scale-free, exponential random graphs, Fiedler random fields), subgraph sampling algorithms (random walk, snowball, etc.), and spectral decomposition.

This Java software implements Profile Hidden Markov Models (PHMMs) for protein classification for the WEKA workbench. Standard PHMMs and newly introduced binary PHMMs are used. In addition the software allows propositionalisation of PHMMs.

A paint program where the canvas is the visual cortex of a simple kind of artificial intelligence. You paint with the mouse into its dreams and it responds by changing what you painted gradually. There will also be an API for using it with other programs as a general high-dimensional space. Each pixel's brightness is its own dimension. Bayesian nodes have exactly 3 childs because that is all thats needed to do NAND in a fuzzy way as Bayes' Rule which is NAND at certain extremes. NAND can be...

Conrad is both a high performance Conditional Random Field engine which can be applied to a variety of machine learning problems and a specific set of models for gene prediction using semi-Markov CRFs.

HmmSDK is a hidden Markov model (HMM) software development kit written in Java. It consists of core library of HMM functions (Forward-backward, Viterbi, and Baum-Welch algorithms) and toolkits for application development.

UGLi ML: The Undirected Graphical Library for Machine Learning. Easy, agile learning and inference from structured/relational data using Markov Networks and Conditional Random Fields.