Search Results for "classification" - Page 17
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Showing 576 open source projects for "classification"
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Mélographe
Représentation des modes musicaux
Ce programme offre une représentation du mode musical extrait d'un fichier midi, à des fins d'analyse, classification, comparaison, ou comme support pour l'improvisation. ---------- This small software offers a representation of the musical mode extracted from a midi file, for musical analysis, classification, comparison, or support for improvisations. -
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An online platform for emotion analysis, classification and risk perception analysis in social media data. The platform is a step further towards bridging the gap between: Emotion classification and analysis on one side, and risk perception dissemination analysis on the other side. The platform core values are: - Open source - Ease of use - Extensibility and flexibility
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MCaVoH
A toolkit for classification of human Microbiota
MCaVoH is a toolkit implemented in Matlab for Mining, Classification and Visualization of Human Microbiota. -
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Adaptive Gaussian Filtering
Machine learning with Gaussian kernels.
Libagf is a machine learning library that includes adaptive kernel density estimators using Gaussian kernels and k-nearest neighbours. Operations include statistical classification, interpolation/non-linear regression and pdf estimation. For statistical classification there is a borders training feature for creating fast and general pre-trained models that nonetheless return the conditional probabilities. Libagf also includes clustering algorithms as well as comparison and validation routines. It is written in C++. -
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SpliceJumper
A tool for splicing junction calling from RNA-Seq data
SpliceJumper is classification based splicing junction calling tool. For now, it accepts paired-end RNA-Seq reads as input, and calls out the junctions. Also do the alignment. -
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DynaSys
An easy-to-use dynamical systems modeler with great visualizations.
...Examine a single path or an entire vector field. Change parameters and watch the effects in real time. Load and save models and data. Enter nullclines and Jacobians identification and classification of equilibria. Auto-generate fast C implementations of your model and fit them to data using Matlab, with optional GPU support. The long-term goal is to incorporate this into software that simulates whole neural networks. Note: This is a beta version, and there is currently no user's manual. Additional developers welcome. ... -
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...The prediction of protein"hubs" was done using physiochemical, thermodynamic and conformational properties of amino acid residues from amino acid sequence. Our prediction results show that meaningful amino acid features can produce signature features for differentiating hubs from non-hubs. The classical classification method, Support Vector Machines (SVM), is used to develop a tool to discriminate between hub and non hub proteins. Funding from Department of Information Technology,Govt. of India, (DIT/R&D/B10/15(23)2008, dated 07/09/2010), is acknowledged.
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Collective Mind Technology
plugin-based framework for systematic and reproducible experimentation
...cM uses crowdsourcing to leverage knowledge and computational resources of multiple users. For example, it includes multi-objective GCC, LLVM and ICC auto-tuning scenarios using shared benchmarks, codelets, data sets, tools, and combined with classification and predictive models. cM includes OpenME interactive interface to open up and expose internals of various third-party tools such as GCC, LLVM, run-time systems, etc. and connect them to cM through dynamic plugins that allows online analysis and tuning of programs and architectures. Live repo: http://c-mind.org/repo -
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The JINSECT toolkit is a Java-based toolkit and library that supports and demonstrates the use of n-gram graphs within Natural Language Processing applications, ranging from summarization and summary evaluation to text classification and indexing.
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VADER
Lexicon and rule-based sentiment analysis tool
VADER (Valence Aware Dictionary and sEntiment Reasoner) is a lexicon and rule-based sentiment analysis tool designed for analyzing the sentiment of text, particularly in social media and short text formats. It is optimized for quick and accurate analysis of positive, negative, and neutral sentiments. -
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Clustering Variation looks for a good subset of attributes in order to improve the classification accuracy of supervised learning techniques in classification problems with a huge number of attributes involved. It first creates a ranking of attributes based on the Variation value, then divide into two groups, last using Verification method to select the best group.
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MODLEM
rule-based, WEKA compatible, Machine Learning algorithm
...This algorithm contains some aspects of Rough Set Theory: the class definition can be described accordingly to its lower or upper approximation. For more information, see: Stefanowski, Jerzy. The rough set based rule induction technique for classification problems. In: Proc. 6th European Congress on Intelligent Techniques and Soft Computing, vol. 1. Aachen, 1998. s. 109-113. -
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Fuzzy clustering variation looks for a good subset of attributes in order to improve the classification accuracy of supervised learning techniques in classification problems with a huge number of attributes involved. It first creates a ranking of attributes based on the Variation value, then divide into two groups, last using Verification method to select the best group.Simon Fong, Justin Liang, YanZhuang, "Improving Classification Accuracy Using Fuzzy Clustering Coefficients of Variations (FCCV) Feature Selection Algorithm", 2014 IEEE 15th International Symposium on Computational Intelligence and Informatics (CINTI), pp.147-151
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TUIT
Taxonomic Unit Identification Tool
...Read our paper in Biotechniques: http://www.ncbi.nlm.nih.gov/pubmed/24502797 Taxonomic Unit Identification Tool (TUIT) is a free open source platform-independent software, designed specifically to facilitate taxonomic annotation of nucleotide sequences via BLAST homology search against the NCBI databases. TUIT is immediately applicable for both to 16S microboime studies as well as for taxonomic classification of the nucleotide reads. Please see the project's Wiki page. -
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The SPARE library (Something for PAttern REcognition) is a set of C++ (template) classes that offer some building blocks useful to build software modules for complex Pattern Recognition tasks, as: Classification, Clustering, Function Approximation.
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ConvNetJS
Deep learning in Javascript to train convolutional neural networks
...ConvNetJS is an implementation of Neural networks, together with nice browser-based demos. It currently supports common Neural Network modules (fully connected layers, non-linearities), classification (SVM/Softmax) and Regression (L2) cost functions, ability to specify and train Convolutional Networks that process images, and experimental Reinforcement Learning modules, based on Deep Q Learning. The library allows you to formulate and solve Neural Networks in Javascript. If you would like to add features to the library, you will have to change the code in src/ and then compile the library into the build/ directory. ... -
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Persica-A new Persian corpus for NLP
This project presents a new corpus for NEWS text analysis in Persian
Lack of multi-application text corpus despite of the surging text data is a serious bottleneck in the text mining and natural language processing especially in Persian language. This project presents a new corpus for NEWS articles analysis in Persian called Persica. NEWS analysis includes NEWS classification, topic discovery and classification, category classification and many more procedures. Dealing with NEWS has special requirements and first of all a valid and reliable corpus to perform the experiments on them. Please use this reference to cite us: @inproceedings{eghbalzadeh2012persica, title={Persica: A Persian corpus for multi-purpose text mining and Natural language processing}, author={Eghbalzadeh, Hamid and Hosseini, Behrooz and Khadivi, Shahram and Khodabakhsh, Ali}, booktitle={Telecommunications (IST), 2012 Sixth International Symposium on}, pages={1207--1214}, year={2012}, organization={IEEE} } -
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GeCCO (Genomic CNV Classification Objectively) is a bioinformatics tool for classifying copy number variants as either benign or pathogenic.
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“Arabic Wikipedia into Named Entity Taxonomy” is a dataset consists of 4000 of Arabic Wikipedia articles that classified into coarse-grained NE taxonomy. This dataset can be used in document classification tasks in relation to NER. To use this corpus, please cite the following publication: F. Alotaibi and M. Lee, "Mapping Arabic Wikipedia into the Named Entities Taxonomy", In Proceedings of COLING 2012: Posters, p43-52, IIT, Mumbai, India, December 8-15. 2012. Author URL: http://www.cs.bham.ac.uk/~fsa081/index.html http://fsalotaibi.kau.edu.sa Email: fsalotaibi {AT} kau.edu.sa fsa081 {AT} cs.bham.ac.uk
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SALT
Sensitive and accurate protein domain classification for short reads
SALT is designed to sensitively and accurately classify short sequences into their native protein domain families with extremely low memory usage. -
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BudgetedSVM
BudgetedSVM: A C++ Toolbox for Large-scale, Non-linear Classification
We present BudgetedSVM, a C++ toolbox containing highly optimized implementations of three recently proposed algorithms for scalable training of Support Vector Machine (SVM) approximators: Adaptive Multi-hyperplane Machines (AMM), Budgeted Stochastic Gradient Descent (BSGD), and Low-rank Linearization SVM (LLSVM). BudgetedSVM trains models with accuracy comparable to LibSVM in time comparable to LibLinear, as it allows solving highly non-linear classi fication problems with millions of... -
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LiveLoad
Military Load Classification based on GTA 05-07-13
Liveload is a calculator that automates the algorithm used in US Army GTA 05-07-13 to classify military bridges by load capability, or MLC. -
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Java Machine Learning Library is a library of machine learning algorithms and related datasets. Machine learning techniques include: clustering, classification, feature selection, regression, data pre-processing, ensemble learning, voting, ...
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Code for Semi-Supervised Machine Learning Techniques, Self-Learning and Co-training used in the paper: Rania Ibrahim, Noha A. Yousri, Mohamed A. Ismail and Nagwa M, El-Makky. “miRNA and Gene Expression based Cancer Classification using Self-Learning and Co-Training Approaches”. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 495-498, 2013. --------------------------------------------------------------------------- For Self-Learning: java -jar -Xms1700m SelfLearner.jar [trainFile] [testFile] [labelFile] [unlabeledFile] [Alpha] [ClassifierType(randomforest,svm)] [resultFile] [ClassifierModelFile] For Co-Training: java -jar -Xms2500m CoTraining.jar [trainFile-Side1] [testFile-Side1] [labelFile-Side1] [unlabeledFile-Side1] [trainFile-Side2] [testFile-Side2] [labelFile-Side2] [unlabeledFile-Side2] [MappingFile] [Alpha] [ClassifierType(randomforest,svm)] [resultFile] [ClassifierModelFileSide1] [ClassifierModelFileSide2]
