Search Results for "data collection algorithm" - Page 5

SeleSup is a simple and fast algorithm (O(n^2)) for reducing the training cardinality of data sets through the elimination of irrelevant instances by mimicking the self-regulatory and suppression mechanism found in the immune system.

...It implements both latent SVM training (where part assignments are treated as latent variables) and weak-label structural SVM (WL-SSVM) for learning from partially labeled data. The code integrates several enhancements: a star-cascade detection algorithm to speed up screening, context rescoring (re-ranking detections using contextual information), and various optimizations like in-memory training (rather than large on-disk data files).

KALIMAT a Multipurpose Arabic Corpus We are pleased to announce the immediate availability of KALIMAT 1.0, KALIMAT is an Arabic natural language resource that consists of: 1) 20,291 Arabic articles collected from the Omani newspaper Alwatan by (Abbas et al. 2011). 2) 20,291 Extractive Single-document system summaries. 3) 2,057 Extractive Multi-document system summaries. 4) 20,291 Named Entity Recognised articles. 5) 20,291 Part of Speech Tagged articles. 6) 20,291 Morphologically Analyse articles. The data collection articles fall into six categories: culture, economy, local-news, international-news, religion, and sports. The process of creating KALIMAT was applied to the entire data collection (20,291 articles).

MapPSO is a tool for Ontology Alignment, which uses Discrete Particle Swarm Optimisation. A particle swarm is used to search for the optimal alignment. The algorithm is massively parallel and adapts naturally on parallel architectures.

TreeLiker is a collection of fast algorithms for working with complex structured data in relational form. The data can, for example, describe large organic molecules such as proteins or groups of individuals such as social networks or predator-prey networks etc. The algorithms included in TreeLiker are unique in that, in principle, they are able to search given sets of relational patterns exhaustively, thus guaranteeing that if some good pattern capturing an important feature of the problem exists, it will be found. ...

Darwin 2: Java Framework for Evolutionary Computation (genetic algorithm, GA). A true framework with out-of-the-box functionality and extensibility of all classes. Interface-based pattern with dependency-injection to configure components.

A collection of algorithms based on the topology preserving Neural Gas algorithm for density estimation/quantization/clustering/self-organized learning. I moved this project to GitHub: https://github.com/sergioroa/neuralgas

A fast artificial intelligence library which currently supports: kNN (k-Nearest Neighbor algorithm) MLP (Multilayer-Perceptron)

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. Moreover, it has many significant improvement than CRF++, such as totally parallel encoding, optimizing memory usage and so on. ...

...The repository covers a broad set of topics such as linear regression, logistic regression, neural networks, clustering, support vector machines, and recommender systems. Each folder corresponds to a specific algorithm or concept, making it easy for learners to navigate and practice. The exercises serve as practical, hands-on reinforcement of theoretical concepts taught in the course. This collection is valuable for students and practitioners who want to strengthen their skills in machine learning through coding exercises.

...I'd like to clean it up and improve the back end design when time permits. See the wiki for known issues and more information. A computer vision program for analysis of magnetic data collected by a scanning probe microscope. Originated in summer 2007 as a collection of C compiled for Matlab (MEX) files and was eventually ported to a standalone C++ application with a GUI created in Qt. This program takes atomic and magnetic force microscope (AFM/MFM) image pairs as input and uses threshold segmentation to identify magnetic nanodots by intensity in the AFM image. ...

A unified collection of algorithms for Artificial Life. It includes evolutionary algorithms, neural networks, data mining tools, compilers, among others.

A java implementation of several evolutionary algorithms as part of the Unified Algorithm Collection developed by Jonatan Gomez

Leark is a Data Mining library developed in C#.NET. It contains several methods for ranking web documents described with a set of normalized features, and a feature selection algorithm. The methods are based on perceptron and clustering.

Game Toolbox is a C# assembly designed to facilitate the creation of games and game prototypes. It contains no graphics code, does not depend on XNA, and is Mono-compatible. It provides implementations of A*, GOAP, a genetic algorithm, and more.

This project contains a collection of robotics algorithms and data-processing tools developed and maintained by researchers in the Stanford AI Laboratory (SAIL). The project uses the infrastructure provided by ROS to encourage modularity and reusabil

CEGA is a highly extendable layout plugin for Cytoscape based on an Evolutionary Algorithm. In contrast to other layout algorithms, CEGA lets users decide which features are important for the visualization of their graphs.

Sanchay is a collection of tools and APIs for language researchers. It has some implementations of NLP algorithms, some flexible APIs, several user friendly annotation interfaces and Sanchay Query Language for language resources.

Java package to study a clustering model described in the paper \"Novel Clustering Algorithm Based Upon Games on Evolving Network\" by Q. Li, Z. Chen, Y. He and J-P. Jiang (in arxiv: http://arxiv.org/pdf/0812.5064v1), generalizations and similar issues.

The aim of the project is to provide open source collection of algorithms in the field of spectroscopy: data handling and processing, modeling and artificial intelligence tools.

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.

KNN-WEKA provides a implementation of the K-nearest neighbour algorithm for Weka. Weka is a collection of machine learning algorithms for data mining tasks. For more information on Weka, see http://www.cs.waikato.ac.nz/ml/weka/.

This project intends to create an indexing search engine, for knowledge management. The primary object is to apply an information retrieval core. And implement a knowledge data discovery theory such as data mining algorithm, text mining.

musicomp is a program which most important element is an evolutionary algorithm which uses data mining methods as a fitness function to generate monophone melodies.

Artificial vision library. Objectives are to make an OCR, fingerprint and face identification as some applications through a general purpose learning and pattern relationships algorithm (Currently performs very basic identification).