Search Results for "bayes" - Page 2
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Showing 61 open source projects for "bayes"
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POPFile is an email classification tool with a Naive Bayes classifier, POP3, SMTP, NNTP proxies and IMAP filter and a web interface. It runs on most platforms and with most email clients.
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This site contains four packages of Mass and mass-based density estimation. 1. The first package is about the basic mass estimation (including one-dimensional mass estimation and Half-Space Tree based multi-dimensional mass estimation). This packages contains the necessary codes to run on MATLAB. 2. The second package includes source and object files of DEMass-DBSCAN to be used with the WEKA system. 3. The third package DEMassBayes includes the source and object files of a Bayesian...
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HLearn
Homomorphic machine learning
...This allows for parallel, incremental, and distributed computation in a mathematically consistent way. HLearn aims to provide implementations of common algorithms like k-means, naive Bayes, and others while maintaining the expressiveness and safety of the Haskell language. -
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Document Classification
Document/Text Classification using Naive Bayes model.
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vbTPM
Variational Bayes for tethered particle motion
vbTPM is an analysis package aimed at analyzing time series from a single molecule technique called tethered particle motion, which are common for in vitro investigations of protein-nucleic acid interactions. vbTPM uses a variational approach to hidden Markov models, and resembles recent methods for single molecule FRET (http://vbfret.sourcefore.net/) and single particle tracking (http://vbspt.sourceforge.net/) data. 2014-08-12: NAR manuscript in print!... -
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Bayes' decision, Fishers criterion
Bayes' decision for minimum risk and Fisher's criterion for two-class
There are two programs here. The first demonstrates the Bayes' decision rule for minimum risk. The second demonstrates Fisher's criterion for two-class discrimination. -
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TextBlob
TextBlob is a Python library for processing textual data
Simple, Pythonic, text processing, Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more. It provides a simple API for diving into common natural language processing (NLP) tasks such as part-of-speech tagging, noun phrase extraction, sentiment analysis, classification, translation, and more. TextBlob stands on the giant shoulders of NLTK and pattern, and plays nicely with both. Supports word inflection (pluralization and singularization) and lemmatization,... -
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Grindstone4Spam
Tools for optimising SpamAssassin
Grindstone for Spam1.0 is an open source, lightweight tool set designed to aid on develop SpamAssasintm based filters and improve the general performance of them. It includes features such as optimization of scores asigned to rules, offline evaluation of filter, reduction of unuseful terms stored at bayes database and offline regex evaluation. The toolkit has been developed using Perl, C and bash scripting. -
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ScientificPdfParser
Parses scientific articles from PDF and marks the meta data.
Parses PDF files of scientific articles based on naive bayes and sophisticated heuristics. The output is a XML file that contains the parsed data. Meta data is detected and marked as such. The meta data contains the following elements: - Title - Authors - Abstract - Text - Headlines - Enumerations - References (Literature) In the first step, the text elements are divided into blocks (similar to paragraphs) and after that, predictions for each element are made. ... -
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Averaged N-Dependence Estimators - AnDE
AnDE implements A1DE and A2DE
Averaged N-Dependence Estimators (A1DE and A2DE) achieves highly accurate classification by averaging over all of a small space of alternative naive-Bayes-like models that have weaker (and hence less detrimental) independence assumptions than naive Bayes. The resulting algorithm is computationally efficient while delivering highly accurate classification on many learning tasks. For more information, see, G. Webb, J. Boughton, Z. Wang (2005). Not So Naive Bayes: Aggregating One-Dependence Estimators. ... -
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AdPreqFr4SL
Adaptive Prequential Learning Framework
The AdPreqFr4SL learning framework for Bayesian Network Classifiers is designed to handle the cost / performance trade-off and cope with concept drift. Our strategy for incorporating new data is based on bias management and gradual adaptation. Starting with the simple Naive Bayes, we scale up the complexity by gradually updating attributes and structure. Since updating the structure is a costly task, we use new data to primarily adapt the parameters and only if this is really necessary, do we adapt the structure. The method for handling concept drift is based on the Shewhart P-Chart. Project homepage: http://adpreqfr4sl.sourceforge.net -
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Weighted Naive Bayes
Attribute Weighting for Naive Bayes
Despite the simplicity and naive assumption of the Naive Bayes classifier, it has continued to perform well against more sophisticated newcomers and has remained, therefore, of great interest to the machine learning community. Of numerous approaches to refining the naive Bayes classifier, attribute weighting has received less attention than it warrants. Most approaches,perhaps influenced by attribute weighting in other machine learning algorithms, use weighting to place more emphasis on highly predictive attributes than those that are less predictive. ... -
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Averaged N-Dependence Estimators (A1DE and A2DE) achieves highly accurate classification by averaging over all of a small space of alternative naive-Bayes-like models that have weaker (and hence less detrimental) independence assumptions than naive Bayes. The resulting algorithm is computationally efficient while delivering highly accurate classification on many learning tasks. For more information, see, G. Webb, J. Boughton, Z. Wang (2005). Not So Naive Bayes: Aggregating One-Dependence Estimators. ...
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Open Bayes is a python free/open library that allows users to easily create a bayesian network and perform inference/learning on it. It is mainly inspired from the Bayes Net Toolbox (BNT) but uses python as a base language. www.openbayes.org
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Iris
Iris is a web based bayes data classifier.
Iris is a web based classification system. The system is a bayes classifier and calculates (and compare) the decision based upon conditional probability of the decision options. This system currently classify 3 groups of flowers from the iris dataset depending upon a few selected features. The concept which makes Iris stand out is the use of a 'window'. A window is incorporated along with the threshold while sampling. -
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A general purpose Bayesian Network Toolbox. This project seeks to take advantage of Python's best of both worlds style and create a package that is easy to use, easy to add on to, yet fast enough for real world use.
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BayesianCortex
simple algorithm for a realtime interactive visual cortex for painting
...There will also be an API for using it with other programs as a general high-dimensional space. Each pixel's brightness is its own dimension. Bayesian nodes have exactly 3 childs because that is all thats needed to do NAND in a fuzzy way as Bayes' Rule which is NAND at certain extremes. NAND can be used to create any logical system. In this early version, I'm still working on edge detection and its understanding of the same shapes at different brightnesses. This will be a module of the bigger Human AI Net project and will be used for adding realtime intuitive high dimensional intelligence in audio and visual interactions with the user. -
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MultiViL is a tool for multi-view learning. It supports four classifiers (KNN, Naive-Bayes, Rochio and SVM-Perf), four view combining methods (Majority Voting, Borda Count, Dempster-Shafer theory of evidence and PSO) and provides many analisys tools.
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Sasa is a segmentator and symmetry analyser tool, you can segment your pictures and count symmetry with many algorithms, you can use Laws filters, and Markov segmentation with Bayes decision.
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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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Projeny (Probablistic Networks Generator in Java) is a graphical (Java SWT) front-end to BNT (Bayes Net Toolbox for Matlab). Projeny requires BNT, JMatLink and a Matlab back-end. There is no installable release package, but source code is available on SVN - please check out from SVN to use Projeny. Projeny was started with BNJ as the base.
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AI Magik is a templatized C++ library providing basic predictors for supervised learning as reusable modules. Currently, the library features CNF Predictor, DNF predictor, decision tree, naive bayes, linear separator and SVM based predictors.
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software for identifying modules in networks (e.g. "community detection"), as described in "a bayesian approach to network modularity" (physical review letters 100, 258701 (2008); http://link.aps.org/abstract/PRL/v100/e258701).
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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.
