Search Results for "classification" - Page 19
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Showing 644 open source projects for "classification"
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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]
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webtextanalysis
Mining knowledge from text data
This project aims to implement in java the following text mining techniques: Text Language Detection, Keywords and keyphrases extraction, Text Classification, Text Clustering, Single or multiple documents Summarization, Plagiarism Detection. -
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...This package adapts the following 5 algorithms for classifying and predicting gene expression data using prior knowledge: 1) average gene expression of pathway (aep); 2) pathway activities classification (PAC); 3) Hub network classification (hubc); 4) filter via top ranked genes (FrSVM); 5) network smoothed t-statistic (stSVM).
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The Apelon DTS (Distributed Terminology System) is an integrated set of open source components that provides comprehensive terminology services in distributed application environments.
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RDP FrameBot is a frameshift correction and nearest neighbor classification tool for use with high-throughput amplicon sequencing. It uses a dynamic programming algorithm to align each query DNA sequence against a set of target protein sequences, produces frameshift-corrected protein and DNA sequences and an optimal global or local protein alignment. It also helps filter out non-target reads. The online version of FrameBot is available on http://fungene.cme.msu.edu/FunGenePipeline, tutorial http://rdp.cme.msu.edu/tutorials/framebot/RDPtutorial_FRAMEBOT.html. ...
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Protdraw
Create portable, flexible domain drawings of protein sequences
...ProtDraw is accompanied by makeProtDraw, a helper program which runs hmmer3 on a specified set of hidden Markov models and formats results for ProtDraw. Highest-scoring domains are selected in cases of overlap. Domain drawings may be organized by sequence classification. -
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ImageSorterBOW
Program for classification and sort images by contest.
Program for classification and sort images by contest. It is based on implementation OpenCV Bag of visual world method. -
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Cost-sensitive Classifiers
Adaboost extensions for cost-sentive classification
...Minimum expected cost criteria Input also requires to load an arff file and a cost matrix (sample arff and cost files are uploaded for users' reference) This extension uses weka for classification and generates the classification model along with confusion matrix. For given dataset and cost matrix -
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CalPCS
A pitch class set analyzer.
...System requeriments: Java Runtime Environment 1.6 or above. Screen of at least 800x600px. Optional: A Java Sound Bank. The program displays for each set their normal order, classification, transposition, whether it is an inversion, prime form, interval vector and the invariant property. -
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Graphlet kernel framework
Calculates similarity between neighborhoods of two vertices in a graph
...The list of available similarity functions includes: cumulative random walk, standard random walk, standard graphlet kernel, edit distance graphlet kernel, label substitution graphlet kernel and edge indel graphlet kernel. The graphlet kernel framework can be used for vertex (node) classification in graphs, kernel-based clustering, or community detection. If you use this framework, please cite the following paper: Lugo-Martinez J, Radivojac P. Generalized graphlet kernels for probabilistic inference in sparse graphs. Network Science (2014) 2(2): 254-276. -
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Beryllium¹º is a program designed to facilitate the creation of group safety data sheets (GSDSs) for hazardous substances and processes. The created GSDSs fulfill the conditions of EG Nr. 1272/2008 (Globally Harmonized System of Classification and Labelling of Chemicals, GHS) and §20 Gefahrenstoffverordnung (German regulation and version of European Union Directive 67/548/EEC: Safety advice concerning dangerous substances and preparations).
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FSCAET
Flight Safety Classification and Evaluation Tool
Flight Safety Classification and Evaluation tool allows for evaluation of an airplane flight which is based on recorded data. The tool design is divided into five main parts: flight state classification, flight envelope (limits) tests, terrain collision determination, flight maneuver detection and airspace violation test. It provides a report describing the violated conditions of the flight. -
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LPCforSOS is a machine learning framework with a special focus on structured output spaces and pairwise learning. It supports currently multiclass, ordinal, hierarchical, multi-label and label ranking classification settings.
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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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ANU Project - Summarization Evaluation
This is all my work from my Summer Research Project At ANU
This is all my work from my Summer Research Project At ANU. My project is Verbose Patent Classification. I worked with Dr Gabriella Ferraro. -
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Fast Matrix for Java
General purpose matrix utilities for Java in Parallel Computing
Fast Matrix for Java (fm4j) is a general-purpose matrix utility library for computing with dense matrices. fm4j encapsulated different underlying implementations and select the optimal one in run-time depending on the size of the input matrix. Moreover, fm4j employs Java (Tm) Concurrency to take advantage of the computation power of multi-cor processors. -
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TextBlob
TextBlob is a Python library for processing textual data
...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, as well as spelling correction. Add new models or languages through extensions. Also, it comes with a WordNet integration. If you only intend to use TextBlob’s default models (no model overrides), you can pass the lite argument. ... -
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UnitManager
Simple class used to lead with units classification
Simply provides numeric labels to different metrical and imperial (urgh!) units, like meters, centimeters, liters, feet (argh!)... -
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SecStAnT
Secondary Structure Analysis Tool for data selection and statistics
SecStAnT is a tool for the automatic creation of data-sets of structures from Protein Data Bank (PDB) with user-defined structural composition, and for the calculation of their internal variables distributions. SecStAnT is able to 1. Select from PDB data sets of structures based on user specified secondary structures (defined based on internal PDB classification or on DSSP) and/or sequence motives. 2. Build Data-sets at different levels of resolution (all atoms, only backbone, only Cα, ...) 3. Evaluate statistical distributions of internal variables: a. single variable distributions (including the most relevant in the atomistic representation, e.g. PHI and PSI and a number of those for the Cα based representation) b. two variables correlations (including the PHI-PSI Ramachandran map and its equivalent in the Cα based representation) c. three variables correlations -
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avimmir
(audio, video, image) Multimedia Multimodal Information Retrieval
audio classification; speaker segmentation; speaker clustering; speaker recognition; spoken document retrieval; image retrieval; video retrieval; etc.
