Search Results for "knn algorithm"
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Showing 8 open source projects for "knn algorithm"
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HubSpot is an AI-powered customer platform with all the software, integrations, and resources you need to connect your marketing, sales, and customer service. HubSpot's connected platform enables you to grow your business faster by focusing on what matters most: your customers.
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The only software you need to increase cash flow, optimize resource utilization, and take control of your assets and inventory.
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• Objective: Design a Web-based software that predicts the appearance of a new link between two nodes in a social network • Datasets: Dolphin Social Network: https://networkdata.ics.uci.edu/data.php?id=6 • Requirement: Implement the K-NN Algorithm (Section 6.9.1, page 348)
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Iris Classifier
The classifier for iris flowers (data mining)
This implements KNN algorithm. -
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EkNN
Extracting k nearest neighbors for point cloud
Speed up kNN searching algorithm by extracting nearest neighbors diectly other than searching them one by one -
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tiny-AI Library
small and fast C++ library dealing with artificial intelligence
A fast artificial intelligence library which currently supports: kNN (k-Nearest Neighbor algorithm) MLP (Multilayer-Perceptron) -
BrightGauge, a ConnectWise solution, was started in 2011 to fill a missing need in the small-to-medium IT Services industry: a better way to manage data and provide the value of work to clients. BrightGauge Software allows you to display all of your important business metrics in one place through the use of gauges, dashboards, and client reports. Used by more than 1,800 companies worldwide, BrightGauge integrates with popular business solutions on the market, like ConnectWise, Continuum, Webroot, QuickBooks, Datto, IT Glue, Zendesk, Harvest, Smileback, and so many more. Dig deeper into your data by adding, subtracting, multiplying, and dividing one metric against another. BrightGauge automatically computes these formulas for you. Want to show your prospects how quick you are to respond to tickets? Show off your data with embeddable gauges on public sites.
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Basic implementation of K-nearest neighbour Algorithm and the application of KNN to classify protein sequences as transmembrane beta barrel or non-transmembrane beta barrel on the basis of whole sequence amino acid composition given as input.
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gaKnn(Genetic Algorithm Optimized K Nearest Neighbor Classification framework) is a frameowork for KNN optimization with a genetic algorithm. The genetic algothm used for this is JGAP (http://jgap.sourceforge.net/).
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KNN-WEKA provides a implementation of the K-nearest neighbour algorithm for Weka. Weka is a collection of machine learning algorithms for data mining tasks. For more information on Weka, see http://www.cs.waikato.ac.nz/ml/weka/.
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A Visual Studio .NET C++ application can perform machine learning using genetic algorithm, naive bayes, KNN, and Artificial Neural Networks (ANNs) read and processed from any standard ARFF.
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