Search Results for "naive bayes classifier"
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Showing 36 open source projects for "naive bayes classifier"
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The RDP Classifier is a naive Bayesian classifier that can rapidly and accurately provides taxonomic assignments for bacterial and archaeal 16S rRNA sequences, fungal LSU and fungal ITS sequences, with confidence estimates for each assignment. More information and tutorials on how to install, use and retrain RDP Clasifier can be found on at https://github.com/rdpstaff/classifier and John Quensen's blog (https://john-quensen.com/). Citation: 1. Wang Q, Garrity GM, Tiedje JM, Cole JR. Naive...
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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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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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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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Rent Manager SoftwareRent Manager is award-winning property management software built for residential, commercial, and short-term-stay portfolios of any size. The program’s fully customizable features include a double-entry accounting system, maintenance management/scheduling, marketing integration, mobile applications, more than 450 insightful reports, and an API that integrates with the best PropTech providers on the market.
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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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PTM-X
a solfware for predicting posttranslational modification cross-talk
The PTM-X (PTM cross-talk) project is a freely available bioinformatics software platform that allows to calculate the features of PTM pairs and the posterior probabilities of being cross-talk pairs. The prediction model is a naive Bayse classifier that integrats five features: protein sequence distance, tertiary structural distance, co-location in a disordered region, residue co-evolution, and modification co-evolution. An online tool is also available at http://bioinfo.bjmu.edu.cn/ptm-x/. -
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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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faif
C++ header only library with AI and bioinformatics algorithms
C++ header only library, small and fast; Naive Bayesian Classifier, Decision Tree Classifier (ID3), DNA/RNA nucleotide second structure predictor, timeseries management, timeseries prediction, generic Evolutionary Algorithm, generic Hill Climbing algorithm and others. -
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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...
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This is an interactive and demonstrative implementation of a Naive Bayes probabilistic classifier that can be applied to virtually any machine learning/classification/prediction application.
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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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libtext_bayes
Naive Bayes algorithm text classifier C++ library...
This is a Naive Bayes text classifier library to C++, you can classify SPAM messages, genes, sentiment types in texts. Naive Bayes has been studied extensively since the 1950s. It was introduced under a different name into the text retrieval community in the early 1960s, and remains a popular (baseline) method for text categorization, the problem of judging documents as belonging to one category or the other (such as spam or legitimate, sports or politics, etc.) with word frequencies... -
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... classifier using DEMass. DEMassBayes.7z has jar file to be used with WEKA and a readme file listing parameters used. The source files are included in DEMassBayes_Source.7z. 4. The four package is MassTER includes source and JAR file to be used with WEKA system..
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BAGEL: analysis of gene knockout screens
BAGEL: Bayesian Analysis of Gene EssentiaLity
BAGEL: software for Bayesian analysis of gene knockout screens using pooled library CRISPR or RNAi. BAGEL is a Bayesian classifier for pooled library genetic perturbation screens, using either CRISPR-Cas9 or shRNA libraries. It uses training sets of known essential and nonessential genes to estimate what the fold change distribution of an essential or nonessential gene should look like. Then, for each uncharacterized gene, it takes all observations of reagents targeting that gene (guide RNA... -
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Document Classification
Document/Text Classification using Naive Bayes model.
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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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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... -
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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... -
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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... -
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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...
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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. The window helps using a small dataset and emulate more samples...