Search Results for "matlab text classification" - Page 7

...It can be run in batch mode. It supports a wide array of binary file formats as well as ASCII text.

CRUMp is based on a kernel-based learning method called Classification Relevance Units Machine (CRUM). Given an input set of protein sequences in FASTA format, the system outputs the position, residue type (S, T, or Y), and the estimated probability of each tested site being phosphorylatable. Latest downloadable files: - crump-0.2.0.tar.gz: CRUMp GNU Octave package - crump-0.2.0.zip: CRUMp MATLAB script - crumptestset.fasta: A testing dataset in FASTA format.

This MATLAB tool / GUI allows you to process time series (digital repeat photography) of vegetation and extract a smoothed time series of the greenness of this vegetation across a growing season. The software allows you to select multiple regions of interest (save and load these) and output the resulting smoothed data series to text file for further processing and statistics.

The Stanford Machine Learning Course Exercises repository contains programming assignments from the well-known Stanford Machine Learning online course. It includes implementations of a variety of fundamental algorithms using Python and MATLAB/Octave. 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...

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.

Ragnarok Online Site Engine (ROse) - Free Control Panel (CMS) for eAthena Ragnarok Online server Emulator. Written in PHP language. Use smarty php class for templates. contains many functions for manage eAthena dabases.

...These features comprise sound including parts-of-speech, accent, phoneme, stress, tone, break index. ProseVis allows a reader to map the features extracted from OpenMary (http://mary.dfki.de/) Text-to-speech System and predictive classification data to the "original" text. We developed this project with the ultimate goal of facilitating a reader's ability to analyze and disseminate the results in human readable form. Research has shown that mapping the data to the text in its original form allows for the kind of human reading that literary scholars engage: words in the context of phrases, sentences, lines, stanzas, and paragraphs. ...

A fast, configurable faceted classification and browsing tool for large collection of unstructured data. Its major features include multi-faceted search, hit counts, term highlights and population of free text search results into facets. An AJAX app.

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.

This is a c-library that provides tools for advanced analysis of electrophysiological data. It features denoising, unsupervised classification, time-frequency analysis, phase-space analysis, neural networks, time-warping and more.

Modular Text-to-Speech system with a Matlab backbone. Your modules can be attached to this backbone via executable files (independent of the programming language used) respecting the XML interface requirements.

Provides a set of tools for processing text, such as text extraction and classification. Classification implementations to be implemented include: Bayesian and Statistical (N-gram).

An information extraction library implementing modern algorithms for the extraction of named entities from text.

An Artificial Intelligence based software written in Java, deployed as an EJB / WebService application and implementing neural networks for data processing. It aims to be the brain of the web by serving text classification, mood detectors, etc.

A lyrical analysis and classification tool focused specifically on rhyming style in rap lyrics. Functions include phonetic transcription, rhyme visualization, and rapper classification.

Image and video acquisition for scientific applications, particularly in behavioral biology and neuroscience

This application allows to generate graphics from data file in table format and a graphical configuration file XML..

A tool to aid in the execution of Systematic Mapping Studies.

This is the beginning of a Blade Element Momentum Theory code that I have developed for my own research. It currently includes tip loss, twist, taper, and altitude correction. The MATLAB version also includes a combined vortex panel method.

Search and export numerics from any text/ascii file. Data sets (scalar, vector, matrix) are given unique names, based on file content. Results can be generated for Matlab, IDL, Scilab, Octave, XML, HTML A wrapper exists for direct usage from Matlab.

Implematation of robust depth-based inference tools for microarray data (a scale curve, to measure the dispersion of a set of curves, a rank test to decide if two groups of curves come from the same population, and classification techniques).

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.

Matlab Classification Toolbox contains implementations of the following classifiers: Naive Bayes, Gaussian, Gaussian Mixture Model, Decision Tree and Neural Networks. This toolbox allows users to compare classifiers across various data sets.

The Databionics ESOM Tools offer many data mining tasks using Emergent Self-Organizing Maps. Visualization, clustering, and classification of high-dimensional data using databionics principles can be performed interactively or automatically.

Notebook mode sets up a sub-process that has well defined input and output responses, such as a shell, or a command line program like matlab. Each notebook has a collection of cells, consisting of a prompt, an input region, and an output region.