Search Results for "bayes"
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Showing 70 open source projects for "bayes"
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Bayes+Estimate is a Rust and C++ library that implement numerical algorithms for Bayesian estimation. They provide tested and consistent numerical methods and represents the wide variety of Bayesian estimation algorithms and system model.
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MatlabMachine
Machine learning algorithms
Matlab-Machine is a comprehensive collection of machine learning algorithms implemented in MATLAB. It includes both basic and advanced techniques for classification, regression, clustering, and dimensionality reduction. Designed for educational and research purposes, the repository provides clear implementations that help users understand core ML concepts. -
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Python 100 Days
Python - From Novice to Master in 100 Days
.... The curriculum expands into databases and SQL, Linux essentials, web fundamentals, and a substantial Practical Django track that covers ORM, sessions, RESTful APIs, caching with Redis, asynchronous tasks with Celery, authentication, testing, and deployment. Data analysis and visualization receive dedicated coverage via NumPy, pandas, matplotlib, seaborn, and pyecharts, followed by an applied machine learning track with kNN, trees, Bayes, regression, clustering, ensembles, and neural networks. -
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pomegranate
Fast, flexible and easy to use probabilistic modelling in Python
... networks can be dropped into a mixture just as easily as a normal distribution, and hidden Markov models can be dropped into Bayes classifiers to make a classifier over sequences. Together, these two design choices enable a flexibility not seen in any other probabilistic modeling package. -
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Bayesian Statistics
This repository holds slides and code for a full Bayesian statistics
This repository holds slides and code for a full Bayesian statistics graduate course. Bayesian statistics is an approach to inferential statistics based on Bayes' theorem, where available knowledge about parameters in a statistical model is updated with the information in observed data. The background knowledge is expressed as a prior distribution and combined with observational data in the form of a likelihood function to determine the posterior distribution. The posterior can also be used... -
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Bayesian Julia
Bayesian Statistics using Julia and Turing
Bayesian statistics is an approach to inferential statistics based on Bayes' theorem, where available knowledge about parameters in a statistical model is updated with the information in observed data. The background knowledge is expressed as a prior distribution and combined with observational data in the form of a likelihood function to determine the posterior distribution. The posterior can also be used for making predictions about future events. Bayesian statistics is a departure from... -
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natural
General natural language facilities for node
"Natural" is a general natural language facility for nodejs. It offers a broad range of functionalities for natural language processing. Tokenizing, stemming, classification, phonetics, tf-idf, WordNet, string similarity, and some inflections are currently supported. It’s still in the early stages, so we’re very interested in bug reports, contributions and the like. Note that many algorithms from Rob Ellis’s node-nltools are being merged into this project and will be maintained from here... -
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RASP
RASP (Reconstruct Ancestral State in Phylogenies)
RASP (Reconstruct Ancestral State in Phylogenies) is a tool for inferring ancestral state using S-DIVA (Statistical dispersal-vicariance analysis), Lagrange (DEC), Bayes-Lagrange (S-DEC), BayArea, BBM (Bayesian Binary MCMC) method, Bayestraits and BioGeoBEARS packages. All documentation and source code for RASP is freely available at: http://mnh.scu.edu.cn/soft/blog/RASP and http://github.com/sculab/RASP -
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UnBBayes
Framework & GUI for Bayes Nets and other probabilistic models.
UnBBayes is a probabilistic network framework written in Java. It has both a GUI and an API with inference, sampling, learning and evaluation. It supports Bayesian networks, influence diagrams, MSBN, OOBN, HBN, MEBN/PR-OWL, PRM, structure, parameter and incremental learning. Please, visit our wiki (https://sourceforge.net/p/unbbayes/wiki/Home/) for more information. Check out the license section (https://sourceforge.net/p/unbbayes/wiki/License/) for our licensing policy. -
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MailCleaner
Anti Spam SMTP Gateway
MailCleaner Open Source Edition is now discontinued but will continue under the spamtagger project https://github.com/SpamTagger [antispam] MailCleaner is an anti-spam / anti-virus filter SMTP gateway with user and admin web interfaces, quarantine, multi-domains, multi-templates, multi-languages. Using Bayes, RBLs, Spamassassin, MailScanner, ClamAV. Based on Debian. Enterprise ready. MailCleaner is an anti spam gateway installed between your mail infrastructure and the Internet... -
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Bayes Anti-Spam
Anti Spam AddIn / Plugin for Outlook
For Outlook I had been using the SpamBayes plugin for years in order to remove spam e-mails. However, with Outlook 365 the addin stopped working for me. This reimplementation enables you to mark e-mails as spam or valid. Based on your input the addin learns how to classify e-mails. If the addin detects spam then it will move the e-mail to a configurable folder in Outlook. E-mails for which the decision is uncertain will be moved to another configurable folder. -
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MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack
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Version2. to cite this collection: DOI: http://dx.doi.org/10.12785/ijcds/100161 title={A Combined Method of Naïve-Bayes and Pooling Strategy for Building Test Collection for Arabic/English Information Retrieval}, author={Mazari, Ahmed Cherif and Djeffal, Abdelhamid}, journal={International Journal of Computing and Digital Systems}, volume={10}, year={2021}, publisher={University of Bahrain} }
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Think Bayes
Code repository for Think Bayes
ThinkBayes is the code repository accompanying Think Bayes: a book on Bayesian statistics written in a computational style. Instead of heavy focus on continuous mathematics or calculus, the book emphasizes learning Bayesian inference by writing Python programs. The project includes code examples, scripts, and environments that correspond to the chapters of the book. Learners can run the code, experiment with probability distributions, compute posterior probabilities, and understand Bayesian... -
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vbTRACK_2D
Bayesian analysis of 2D(x,y) time series particle tracks using Matlab.
Matlab program analyzes 2D (xy) time-series data (tracks) by variaional Bayes, hidden Markov, Gaussian mixture pattern recognition pattern recognition methods. It finds the number of states, the position of each state, and assigns each time-point to its most probable specific state. -
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DEBay
Deconvolutes qPCR data to estimate cell-type-specific gene expression
DEBay: Deconvolution of Ensemble through Bayes-approach DEBay estimates cell type-specific gene expression by deconvolution of quantitative PCR data of a mixed population. It will be useful in experiments where the segregation of different cell types in a sample is arduous, but the proportion of different cell types in the sample can be measured. DEBay uses the population distribution data and the qPCR data to calculate the relative expression of the target gene in different cell types... -
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Probability Cheatsheet
A comprehensive 10-page probability cheatsheet
The probability_cheatsheet is a cheat sheet repository that summarizes key probability theory concepts, formulas, distributions, and properties in a concise format. It likely includes definitions of random variables, PMFs and PDFs, expectations, variance, common distributions (e.g. binomial, normal, Poisson, exponential), conditional probability, Bayes’ theorem, moment generating functions, and perhaps important inequalities (Markov, Chebyshev, Chernoff). The cheat sheet is intended as a quick... -
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GSMLBook
Recipes for basic machine learning algorithms using sklearn in jupyter
... descent); classification and regression trees; random forests; neural networks; probabilistic methods (KNN, naive Bayes', QDA, LDA); dimensionality reduction with PCA; support vector machines; and clustering with K-Means, hierarchical, and DBScan. Appendices provide a review of probability and linear algebra. While some mathematical foundation is provided, it is not essential for understanding the implementations. The target audience is advanced community college and university students. -
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CodeView
Display code with syntax highlighting in native way
CodeView helps to show code content with syntax highlighting in native way. -
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DSTK - Data Science TooKit 3
Data and Text Mining Software for Everyone
DSTK - Data Science Toolkit 3 is a set of data and text mining softwares, following the CRISP DM model. DSTK offers data understanding using statistical and text analysis, data preparation using normalization and text processing, modeling and evaluation for machine learning and algorithms. It is based on the old version DSTK at https://sourceforge.net/projects/dstk2/ DSTK Engine is like R. DSTK ScriptWriter offers GUI to write DSTK script. DSTK Studio offers SPSS Statistics like GUI... -
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Accord.NET Framework
Scientific computing, machine learning and computer vision for .NET
The Accord.NET Framework provides machine learning, mathematics, statistics, computer vision, computer audition, and several scientific computing related methods and techniques to .NET. The project is compatible with the .NET Framework. NET Standard, .NET Core, and Mono. -
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DSTK - DataScience ToolKit
DSTK - DataScience ToolKit for All of Us
DSTK - DataScience ToolKit is an opensource free software for statistical analysis, data visualization, text analysis, and predictive analytics. Newer version and smaller file size can be found at: https://sourceforge.net/projects/dstk3/ It is designed to be straight forward and easy to use, and familar to SPSS user. While JASP offers more statistical features, DSTK tends to be a broad solution workbench, including text analysis and predictive analytics features. Of course you may specify... -
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vbSPT
variational Bayes single particle tracking
vbSPT is an acronym for variational Bayes single particle tracking, a software package for hidden Markov Model analysis of single particle tracking data, primarily for biophysical applications. Journal reference: Extracting intracellular diffusive states and transition rates from single-molecule tracking data. Fredrik Persson, Martin Lindén, Cecilia Unoson & Johan Elf. Nature Methods (2013). doi:10.1038/nmeth.2367 http://www.nature.com/nmeth/journal/vaop/ncurrent/abs/nmeth.2367.html -
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Problem Description: 20 newsgroup Classification problem Bayesian learning for classifying net news text articles: Naive Bayes classifiers are among the most successful known algorithms for learning to classify text documents. We will provide a data set containing 20,000 newsgroup messages drawn from the 20 newsgroups. The dataset contains 1000 documents from each of the 20 newsgroups. 1. For classes descriptions, please refer Table 6.3 of Dr. Mitchell's book (Machine Learning, Tom...
