Search Results for "clustering algorithm matlab"
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Showing 6 open source projects for "clustering algorithm matlab"
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Estimating Software for Heavy ConstructionBuilt by an estimator, SharpeSoft Estimator is a fully comprehensive software that allows for a more efficient and quicker job-winning bids. Ideal for civil, utility, heavy/highway, grading, excavating, paving, and pipeline contractors, SharpeSoft Estimator offers advanced features such as Item Master, Subcontractor Comparison, Materials Comparison, Grouped Items, Trench Profiler, Haul Calculations, What-if Scenarios, Batch Reports, and more.
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Homemade Machine Learning
Python examples of popular machine learning algorithms
homemade-machine-learning is a repository by Oleksii Trekhleb containing Python implementations of classic machine-learning algorithms done “from scratch”, meaning you don’t rely heavily on high-level libraries but instead write the logic yourself to deepen understanding. Each algorithm is accompanied by mathematical explanations, visualizations (often via Jupyter notebooks), and interactive demos so you can tweak parameters, data, and observe outcomes in real time. The purpose is pedagogical: you’ll see linear regression, logistic regression, k-means clustering, neural nets, decision trees, etc., built in Python using fundamentals like NumPy and Matplotlib, not hidden behind API calls. ... -
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yafu
Automated integer factorization
...The automation within YAFU is state-of-the-art, combining factorization algorithms in an intelligent and adaptive methodology that minimizes the time to find the factors of arbitrary input integers. Most algorithm implementations are multi-threaded, allowing YAFU to fully utilize multi- or many-core processors (including SNFS, GNFS, SIQS, and ECM). YAFU is primarily a command-line driven tool. You provide the number to factor and, via screen output and log files, YAFU will provide you the factors. There is also an interactive environment similar to MATLAB or PARI/GP, where you can type commands and store results. ... -
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node2vec
Learn continuous vector embeddings for nodes in a graph using biased R
The node2vec project provides an implementation of the node2vec algorithm, a scalable feature learning method for networks. The algorithm is designed to learn continuous vector representations of nodes in a graph by simulating biased random walks and applying skip-gram models from natural language processing. These embeddings capture community structure as well as structural equivalence, enabling machine learning on graphs for tasks such as classification, clustering, and link prediction. ... -
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CRFasRNN
Semantic image segmentation method described in the ICCV 2015 paper
...Our work allows computers to recognize objects in images, what is distinctive about our work is that we also recover the 2D outline of objects. Currently we have trained this model to recognize 20 classes. This software allows you to test our algorithm on your own images – have a try and see if you can fool it, if you get some good examples you can send them to us. CRF-RNN has been developed as a custom Caffe layer named MultiStageMeanfieldLayer. Usage of this layer in the model definition prototxt file looks the following. Check the matlab-scripts or the python-scripts folder for more detailed examples. -
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cCNN
A fast implementation of LeCun's convolutional neural network
Code of this library is partialy based on myCNN MATLAB class written by Nikolay Chemurin. -
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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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