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A K-means clustering implementation for Python, Matlab and C. This algorithm yields the very same solution as standard Kmeans, even after each iteration. However it uses some triangle inequalities [...]
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Locally Weighted Projection Regression (LWPR) is a recent algorithm that achieves nonlinear function approximation in high dimensional spaces with redundant and irrelevant input dimensions. At its [...]
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SHARK is a modular C++ library for the design and optimization of adaptive systems. It provides methods for linear and nonlinear optimization, in particular evolutionary and gradient-based [...]
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We introduce mlpy, a high-performance Python package for predictive modeling. It makes extensive use of NumPy to provide fast N-dimensional array manipulation and easy integration of C code. Mlpy [...]
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The SHOGUN machine learning toolbox's focus is on large scale kernel methods and especially on Support Vector Machines (SVM). It comes with a generic interface for SVMs, features several SVM and [...]
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This is a C++ software designed to train large-scale SVMs for binary classification. The algorithm is also implemented in parallel (PGPDT) for distributed memory, strictly coupled multiprocessor [...]
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RapidMiner (formerly YALE) is one of the most widely used open-source data mining suites and software solutions due to its leading-edge technologies and its functional range. Applications of [...]
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LIBLINEAR is a linear classifier for data with millions of instances and features. It supports L2-regularized logistic regression (LR), L2-loss linear SVM, L1-loss linear SVM, and multi-class SVM
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Python module to ease pattern classification analyses of large datasets. It provides high-level abstraction of typical processing steps (e.g. data preparation, classification, feature selection, [...]
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PyML is an interactive object oriented framework for machine learning in python with a focus on kernel methods.
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