Search Results for "text mining machine learning with matlab"

GNAT is a BioNLP/text mining tool to recognize and identify gene/protein names in natural language text. It will detect mentions of genes in text, such as PubMed/Medline abstracts, and disambiguate them to remove false positives and map them to the correct entry in the NCBI Entrez Gene database by gene ID. March 2017: We started to upload GNAT output on Medline. See files/results/medline/.

Weka wrapper for the SGM toolkit for text classification and modeling. Provides Sparse Generative Models for scalable and accurate text classification and modeling for use in high-speed and large-scale text mining. Has lower time complexity of classification than comparable software due to inference based on sparse model representation and use of an inverted index. The provided .zip file is in the Weka package format, giving access to text classification. Other functions are usable through...

The Java Data Mining Package (JDMP) is a library that provides methods for analyzing data with the help of machine learning algorithms (e.g. clustering, classification, graphical models, neural networks, Bayesian networks, text processing, optimization).

Moara is a biological text mining tool and consists of a Java library and some auxiliary MySQL databases for gene/protein training and extraction of mentions and its further normalization and disambiguation.