- Referenced in 2757 articles
- Irvine Machine Learning Repository. We currently maintain 251 data sets as a service ... machine learning community. You may view all data sets through our searchable interface ... site for the Repository. The UCI Machine Learning Repository is a collection of databases, domain ... generators that are used by the machine learning community for the empirical analysis of machine...
- Referenced in 1102 articles
- from the book: ”The Elements of Statistical Learning, Data Mining, Inference, and Prediction” by Trevor...
- Referenced in 1061 articles
- C4.5: programs for machine learning. (C4.5 has been superseded by C5.0...
- Referenced in 1007 articles
- users it initially has a much steeper learning curve than a simple subroutine library...
- Referenced in 929 articles
- LIBSVM has gained wide popularity in machine learning and many other areas. In this article...
- Referenced in 799 articles
- entirely based on MATLAB code. Easy to learn : 3 new commands is all the user...
- Referenced in 418 articles
- decision-theoretic generalization of on-line learning and an application to boosting. In the first ... considerably more general class of learning problems. We show how the resulting learning algorithm ... knowledge about the performance of the weak learning algorithm. We also study generalizations ... boosting algorithm to the problem of learning functions whose range, rather than being binary...
- Referenced in 246 articles
- regression, and for the problem of learning a ranking function. The optimization algorithms used ... this version is an algorithm for learning ranking functions [Joachims, 2002c]. The goal ... learn a function from preference examples, so that it orders a new set of objects...
- Referenced in 193 articles
- Scikit-learn: machine learning in python. Scikit-learn is a Python module integrating a wide ... range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised ... problems. This package focuses on bringing machine learning to non-specialists using a general-purpose...
- Referenced in 243 articles
- based fuzzy inference system. The architecture and learning procedure underlying ANFIS (adaptive-network-based fuzzy ... adaptive networks. By using a hybrid learning procedure, the proposed ANFIS can construct an input...
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- powerful features. Authoring tool to create interactive learning materials as web pages. Available in many...
- Referenced in 299 articles
- graphical lasso  is an algorithm for learning the structure in an undirected Gaussian graphical...
- Referenced in 295 articles
- Visual Basic to be relatively easy to learn and use. Visual Basic...
- Referenced in 259 articles
- Knowledge Analysis. WEKA is a popular machine learning workbench with a development life of nearly...
Neural Network Toolbox
- Referenced in 167 articles
- form equation. Neural Network Toolbox supports supervised learning with feedforward, radial basis, and dynamic networks ... also supports unsupervised learning with self-organizing maps and competitive layers. With the toolbox...
- Referenced in 162 articles
- educational use, more so for constructionist learning, at the Learning Research Group (LRG) of Xerox...
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- through college—a tangible, visual way to learn mathematics that increases their engagement, understanding...
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- method introduced by the publications ”A fast learning algorithm for deep belief nets...
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- DistAl: An inter-pattern distance-based constructive learning algorithm Multi-layer networks of threshold logic ... classification systems. A new constructive neural network learning algorithm (DistAl) based on inter-pattern distance ... offers a significant advantage over other constructive learning algorithms that use an iterative (and often ... demonstrate that DistAl compares favorably with other learning algorithms for pattern classification...
- Referenced in 84 articles
- SHOGUN machine learning toolbox. We have developed a machine learning toolbox, called SHOGUN, which ... designed for unified large-scale learning for a broad range of feature types and learning ... offers a considerable number of machine learning models such as support vector machines, hidden Markov ... models, multiple kernel learning, linear discriminant analysis, and more. Most of the specific algorithms...