Search Results for "classification" - Page 2
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Showing 58 open source projects for "classification"
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libVMR
VMR - machine learning library
...libVMR is based on the most popular neural network model with a higher generalization ability from kernel tricks - vector machine by Reshetov (VMR). The library has been designed to learn from data sets. Typical applications here are pattern recognition ( binary classification). -
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Java Machine Learning Library is a library of machine learning algorithms and related datasets. Machine learning techniques include: clustering, classification, feature selection, regression, data pre-processing, ensemble learning, voting, ...
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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.
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TextProcessor
A Java package to preprocess text datasets for posterior text analysis
...Basic topic mining models such as LDA and sparse NMF are also supported. The package can also generate feature files from a given text dataset with LDA and LIBSVM format for posterior procedures such as classification or clustering. The toolkit is also being extended for more advanced text analysis tasks based on natural language processing techniques. -
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feed4weka is an open library that enriches weka (http://www.cs.waikato.ac.nz/ml/weka/), an open source project for data analysis. It integrates new classification and clustering algorithms, and adds the coclustering and outlier detection frameworks
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JBoost is a simple, robust system for classification. JBoost contains implementations of several boosting algorithms in an alternating decision tree framework. In addition, JBoost provides extensible software for adding more learning algorithms.
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Nen
neural network implementation in java
3-layer neural network for regression and classification with sigmoid activation function and command line interface similar to LibSVM. Quick Start: "java -jar nen.jar" -
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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.
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This project aims to build a suite of Natural Language Processing tools. Modules will include corpus indexing and access tools, a part-of-speech tagger, tokenisers, text classification software, etc.
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HSSVM(Hyper-Sphere Support Vector Machines) is a software for solving multi-classification problem, implemented by Java.
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This project aims to implement in java the following text mining techniques: Text Language Detection, Keywords and keyphrases extraction, Text Classification, Text Clustering, Single or multiple documents Summarization, Plagiarism Detection.
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This application illustrates natural language processing using tagged grammars and statistical classification. Outputs are shown with the EMMA specification of the W3C. A viewer is provided to allow for more user-friendly viewing of EMMA results.
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Feating constructs a classification ensemble comprising a set of local models. It is effective at reducing the error of both stable and unstable learners, including SVM. For details see the paper at http://dx.doi.org/10.1007/s10994-010-5224-5.
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An information extraction library implementing modern algorithms for the extraction of named entities from text.
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Maximum entropy is a powerful method for constructing statistical models of classification tasks, such as part of speech tagging in Natural Language Processing. Several example applications using maxent can be found in the OpenNLP Tools Library.
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This project develops a web-based (JSP) Fuzzy Rule-Based Expert System for analyzing ECG (electro cardio gram) signals & diagnosing Tachi-Arrhythmias. Proj. main blocks: inference engine, knowledgebase, KB editor, explanation, and feature extraction.
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NLP4J library is a toolset written in Java for Natural Language Processing. This version is oriented to Document Classification and uses Naive Bayes, TF-IDF, etc. There are also pre-processing tools.
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The Neurpheus Morphological Analyser performs morphological analysis, stemming or word form generation tasks using sophisticated classification methods for an analysis of words unseen in a training dictionary.
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The files contained in this distribution implement a computer vision system for the classification and interpretation of flag semaphore signals. Optionally, the message can be used to send and receive TCP/IP packets using the RFC 4824 protocol.
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backprop1 provides a simple three layer backpropagation neural network implemented in java. There are three demo programs to perform point classification, the XOR problem and character recognition.
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Facilitates data mining/natural language processing experiments to be executed on weblogs, such as classification, clustering and rating. As part of these experiments, it is possible to apply Latent Semantic Analysis.
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T-Rex (Trainable Relation Extraction) is a highly configurable machine learning-based Information Extraction from Text framework, which includes tools for document classification, entity extraction and relation extraction.
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fuzzyweka provides an implementation of a classifier for fuzzy classification based on fuzzy if-then rules for WEKA.This classifier renowned the Simple Fuzzy Grid method proposed by the work of Ishibuchi and Al.
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Genetic Programming (tree structure) predictor within Weka data mining software for both continuous and classification problems.
