Search Results for "multi-threaded" - Page 6

LPCforSOS is a machine learning framework with a special focus on structured output spaces and pairwise learning. It supports currently multiclass, ordinal, hierarchical, multi-label and label ranking classification settings.

Read multi-plates in one image without number limitation. 50-55 millisconds for processing one frame of image. Simplest API The smallest, simplest, fastest Modern ANPR SDK CANPRIC is a modern ANPR/LPR engine, which based on machine learning and high performance computing(HPC). The ambition of CANPRIC is leading the ANPR industry into intelligent times and using the HPC technique to get high speed of processing.

...Moreover, it has many significant improvement than CRF++, such as totally parallel encoding, optimizing memory usage and so on. Currently, when training corpus, compared with CRF++, CRF# can make full use of multi-core CPUs and only uses very low memory, and memory grow is very smoothly and slowly while amount of training corpus, tags increase. with multi-threads process, CRF# is more suitable for large data and tags training than CRF++ now. For example, in machine with 64GB, CRF# encodes model with more than 4.5 hundred million features quickly.

This is a RapidMiner extension replacing the current Weka-Plugin with the updated 3.7.3 Weka-Version. This is basically a branch of the 3.7.3 Version of WEKA wrapped into the old extension. 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

HSSVM(Hyper-Sphere Support Vector Machines) is a software for solving multi-classification problem, implemented by Java.

This project is devoted to the creation of an open source Error-Correcting Output Codes (ECOC) library for the Machine Learning community. The ECOC framework is a powerful tool to deal with multi-class categorization problems.

Multi-Core optimized Perceptron Network is a high-performance artificial neural network specially designed for workstations with multi-core CPUs, implemented as a shared library and coded in C++.

Content Addressable Memory, Multi-Variate Statistics, Data Mining Includes analyzing datasets, extracting patterns, creating empirical expert system. Computes joint probabilities and implements a "belief" as the solution of an equilibrium equation

This program generates customizable hyper-surfaces (multi-dimensional input and output) and samples data from them to be used further as benchmark for response surface modeling tasks or optimization algorithms.

Maui is a multi-purpose automatic topic indexing algorithm. Given a document, Maui automatically identifies its topics. Depending on the task topics are tags, keywords, keyphrases, vocabulary terms, descriptors or Wikipedia titles.

BCAR is a library for the associative classification, which denotes "Boosting Class Association Rules". BCAR provides a general tool for classification tasks with various types of input data.

Java library devoted to handle Genetic Algorithms and Classifier Systems. It has been engineered to be used into agent based simulation models and to search bounded optimal solutions in wide solution spaces. It runs on distributed clusters.