Search Results for "random" - Page 4

This application allow user to predict microemulsion region based on algorithm consisted of artificial neural networks and random forests. Those techniques combined create Decision Support System. Application was created as a part of project K/DSC/000033 subsidy for young researchers from Polish Ministry of Higher Education.

...Not only run the algorithm, but the interface helps you to show the number of nodes explored by the algorithm and the number of steps it takes to solve the game. You can start from a random solvable state or navigate to a state yourself. The interface animates the actions of solving the state and you can change the delay between each action to be able to track, analyze and learn.

Carafe is an implementation of Conditional Random Fields and related algorithms targeted at text processing applications. The latest version, jCarafe, is implemented in Scala and runs on the JVM.

err is a plugin based chatbot designed to be easily deployable, extensible and maintainable. It allows you to start scripts interactively from your chatrooms for any reason: random humour, starting a build, monitoring commits, triggering alerts ... It is really easy to add your own feature. Features Backends support: - XMPP : Tested with hipchat, openfire and Jabber but should be compatible with any standard XMPP servers. - CampFire support - Supports MUCs (chatrooms) - Local Graphical Console (for testing/dev) - Local Text Console (for testing/dev)

CRF is a Java implementation of Conditional Random Fields, an algorithm for learning from labeled sequences of examples. It also includes an implementation of Maximum Entropy learning.

CRFSharp(aka CRF#) is a .NET(C#) implementation of Conditional Random Fields, an machine learning algorithm for learning from labeled sequences of examples. It is widely used in Natural Language Process (NLP) tasks, for example: word breaker, postagging, named entity recognized, query chunking and so on. CRF#'s mainly algorithm is the same as CRF++ written by Taku Kudo. It encodes model parameters by L-BFGS.

...New Features Include: -All the Features of the 3.7.3 Weka Package -Multi-Threaded ensemble learning -An enhancement on the popular RandomForest Learner based on "Dynamic Integration with Random Forests" by Tsymbal et al. 2006 and "Improving Random Forests" by Robnik-Sikonja 2004. -More enhancements to the voting mechanisms in Random Forest -Possibility to output Feature Weights according to the original Breiman Paper 2001

Headrand is a static library wrote in c that contains functions to simulate complex systems or make statistical analysis with a new approach called "random function computing"

This library is the source code for the development of neural networks with dynamic random links, or other systems.

CrfAny is a C++ package for efficient and exact training and inference of Conditional Random Fields over any graphical structure, supporting all feature types (boolean, integer and real) and command line, C++/Python Lib interfaces.

With miao3d you can train a specific Gaussian Markov Random Field (GMRF) that then can be used to estimate a depthmap ("3D"), given an image ("2D"). A GUI allows inspection of the image + depthmap.

CRF++ is a simple, customizable, and open source implementation of Conditional Random Fields (CRFs) for segmenting/labeling sequential data. CRF++ is designed for generic purpose and will be applied to a variety of NLP tasks.

The package implements a variety of tools for categorization of multivariate data such as boosted decision trees, bagging and random forest, bump hunting (PRIM), a multi-class learner and others.

fmbux is the approach of an intelligent appearing playout software for automated private radio stations or private places where radio-like sounding ambience is desired. fmbux is widely configurable by ASCII-files and offers rundown of playlist, random pl

ARGMAX is an open source implementation of structured models; conditional random fields and structural support vector machine.

Random Projection Trees is a recursive space partitioning datastructure which can automatically adapt to the underlying (linear or non-linear) structure in data. It has strong theoretical guarantees on rates of convergence and works well in practice.

Ramugen is a music application which assists in / automates composition along stochastic/indeterminate lines. Comes as a Win32 desktop application and a Borland Delphi component-package. Open Source : full source-code and documentation provided. Very fle

FlexCRFs: A Flexible Conditional Random Fields Toolkit for Labeling and Segmenting Sequence Data (this includes a parallel implementation of CRFs called PCRFs to support training CRF models on massively parallel computer systems).

Random Forest classification implementation in Java based on Breiman's algorithm (2001). It assumes the data is in the form [ X_1, X_2, . . ., X_M, Y ] where Y \in {0, 1, . . ., C}. The user must define M, C, and m initially.

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.

JVnSegmenter is a Java-based and open-source Vietnamese word segmentation tool. The segmentation model was trained on about 8,000 sentences using Conditional Random Fields (FlexCRFs). This tool would be useful for Vietnamese NLP community.

CRFChunker: Conditional Random Fields Phrase Chunker (Phrase Chunking Tool) for English. The model was trained on sections 01..24 of WSJ corpus and using section 00 as the development test set (F1-score of 95.77). Chunking speed: 700 sentences/s

CRFTagger: Conditional Random Fields Part-of-Speech (POS) Tagger for English. The model was trained on sections 01..24 of WSJ corpus and using section 00 as the development test set (accuracy of 97.00%). Tagging speed: 500 sentences/s.

A conditional random field implementation, made for tagging large texts, using features.

VKAS uses genetic programming methods to find out the relationship among a set of independent and dependent variable. It is a problem solver software which uses evolutionary computing methods. When vkas is run, it creates a population of chromosomes at random. This population is then genetically modified and next population is generated. Each population is subjected to fitness calculation and if a suitable answer chromosome is found then vkas stops and the answer is printed. If a suitable answer is not found then the program stops after specified max generations are over.