Search Results for "clustering algorithm" - Page 2
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Showing 58 open source projects for "clustering algorithm"
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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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Machine learning library that performs several clustering algorithms (k-means, incremental k-means, DBSCAN, incremental DBSCAN, mitosis, incremental mitosis, mean shift and SHC) and performs several semi-supervised machine learning approaches (self-learning and co-training). --------------------------------------------------------------------------- To run the library, just double click on the jar file. Also, you can use the following command line: Java -Xms1500m -jar "ML Library.jar"...
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ClusterMX
The ClusterMX program implements various clustering algorithms
The ClusterMX program implements various clustering algorithms including 1) K-Means clustering optimized by random walks; 2) Weighted K-Means (applying force filed to the multidimensional clustering space); 3) EM Clustering Algorithm; 4) Multi-Model Mean Shift Clustering with Random Sampling; 5) Unsupervised K-Wishart clustering. -
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ALCHEMY is a genotype calling algorithm for Affymetrix and Illumina products which is not based on clustering methods. Features include explicit handling of reduced heterozygosity due to inbreeding and accurate results with small sample sizes
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SynergyTwo is ortholog clustering software for both prokaryotic and eukaryotic genomes. It requires Workflow (also available on sourceforge) to manage the computes. It is a reimplementation of the algorithm described in Wapinski et al Bioinformatics 2007.
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Unsupervised TXT classifier
Classify any two TXT documents, no training required - JAVA
...First, over-training and second, shortage of data for a training of categories. Instead, each TXT file is a category on its own, rather than an assigned category. In a way, this is similar to clustering but not really a clustering algorithm since there is some training involved. The summarizer from Classifier4J has been adjusted to accept two inputs (lets call them A and B). Then, the summarizer gets trained with A to summarize a document B, and vice versa. This extracts a relevant structure for both documents (and thus avoids the over-training) which are then compared using the Vector-Space analysis to give a range of belonging of one document to another (and thus avoids the shortage of information). ... -
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VneCplus
虚拟网络映射的仿真器框架
VneCplus是一个虚拟网络映射的仿真器框架，其中实现了NC_DSBA算法，极大地提高了虚拟网络的映射性能。 NC_DSBA（Nodes Clustering and Dynamic Service Balance Awareness Algorithm）虚拟网络映射算法采用节点聚类的策略将虚拟网络请求分割为规模较小的子请求，分而治之，极大地降低了计算复杂度。采用PageRank计算每个节点的负载均衡能力和需求，从而使得虚拟网络请求的映射更趋于均衡，显著提高了虚拟网络映射的收益开销比和承载能力。 -
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qure
software for viral quasispecies reconstruction from next-gen seq. data
...The software performs alignments of sequence fragments against a reference genome, finds an optimal division of the genome into sliding windows based on coverage and diversity and attempts to reconstruct all the individual sequences of the viral quasispecies--along with their prevalence--using a heuristic algorithm, which matches multinomial distributions of distinct viral variants overlapping across the genome division. QuRe comes with a built-in Poisson error correction method and a post-reconstruction probabilistic clustering, both parameterized on given error rates in homopolymeric and non-homopolymeric regions. -
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Enhanced Stable Election Protocol- SEP-E
An enhanced stable election protocol for wireless sensor network
While wireless sensor networks are increasingly equipped to handle more complex functions, in-network processing may require these battery powered sensors to judiciously use their constrained energy to prolong the effective network life time especially in a heterogeneous settings. Clustered techniques have since been employed to optimize energy consumption in this energy constrained wireless sensor networks. We propose an Enhanced-SEP clustering algorithm in a three-tier node scenario to prolong the e ffective network life-time. Simulation results shows that the Enhanced-SEP protocol achieves better performance in this respect, compared to other existing clustering algorithms such as LEACH and SEP in both heterogeneous and homogenous environments. -
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NeuralGas
Self-organized learning
A collection of algorithms based on the topology preserving Neural Gas algorithm for density estimation/quantization/clustering/self-organized learning. I moved this project to GitHub: https://github.com/sergioroa/neuralgas -
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EToS (Efficient Technology of Spike sorting; Extracellular recording To Spike trains) is an open-source system for spike sorting. EToS contains the programs of spike detection, feature extraction and clustering.
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Stanford Machine Learning Course
machine learning course programming exercise
...It includes implementations of a variety of fundamental algorithms using Python and MATLAB/Octave. The repository covers a broad set of topics such as linear regression, logistic regression, neural networks, clustering, support vector machines, and recommender systems. Each folder corresponds to a specific algorithm or concept, making it easy for learners to navigate and practice. The exercises serve as practical, hands-on reinforcement of theoretical concepts taught in the course. This collection is valuable for students and practitioners who want to strengthen their skills in machine learning through coding exercises. -
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EGA
A novel and effictive GA algorithm to solve optimization problem
Classical genetic algorithm suffers heavy pressure of fitness evaluation for time-consuming optimization problems. To address this problem, we present an efficient genetic algorithm by the combination with clustering methods. The high efficiency of the proposed method results from the fitness estimation and the schema discovery of partial individuals in current population and. -
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K-link
Read clustering algorithm which identifies and removes chimeric reads
This project was developed for ESTs. However, there is no reason it cannot be extended for use on amplicon sequences from 454. It is used in conjunction with WCDest clustering software. -
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PocketAnalyzerPCA combines a geometric algorithm for detecting pockets in proteins with Principal Component Analysis and clustering. This enables visualization and analysis of pocket conformational distributions of large sets of protein structures.
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Leark is a Data Mining library developed in C#.NET. It contains several methods for ranking web documents described with a set of normalized features, and a feature selection algorithm. The methods are based on perceptron and clustering.
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BorderFlow implements a general-purpose graph clustering algorithm. It maximizes the inner to outer flow ratio from the border of each cluster to the rest of the graph.
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Fluster is a clustering algorithm for the Google Maps API v3. It manages all your markers on the map and summarizes them to "clustered markers" if there is not enough space around them. Acts like MarkerClusterer for v2.
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Java package to study a clustering model described in the paper \"Novel Clustering Algorithm Based Upon Games on Evolving Network\" by Q. Li, Z. Chen, Y. He and J-P. Jiang (in arxiv: http://arxiv.org/pdf/0812.5064v1), generalizations and similar issues.
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...Purpose is to buid an MP3 player with the lowest possible cost. Works on mono files (going stereo shouldn't be very complicated). Doesn't use Helix. The huffman decoding uses a clustering based algorithm.
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N-stage worm propagated via SSH. It executes commands in a given list of hosts and copies files to them with rsync. The paths for its propagation to the cluster are configurable. It offers a scalable/reliable transport API thanks to its adaptive algorithm
