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- 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...
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- C4.5: programs for machine learning. (C4.5 has been superseded by C5.0...
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- LIBSVM has gained wide popularity in machine learning and many other areas. In this article...
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- 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...
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- organization for the purposes of conducting machine learning and deep neural networks research...
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- Knowledge Analysis. WEKA is a popular machine learning workbench with a development life of nearly...
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- accompany Kevin Murphy’s textbook Machine learning: a probabilistic perspective, but can also be used ... unified conceptual and software framework encompassing machine learning, graphical models, and Bayesian statistics (hence...
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- SHOGUN machine learning toolbox. We have developed a machine learning toolbox, called SHOGUN, which ... 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 ... already widely adopted in the machine learning community and beyond. SHOGUN is implemented...
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- from the training text data and then learns vector representation of words. The resulting word ... many natural language processing and machine learning applications...
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- open source computer vision and machine learning software library. OpenCV was built to provide ... applications and to accelerate the use of machine perception in the commercial products. Being ... computer vision and machine learning algorithms. These algorithms can be used to detect and recognize...
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- package kernlab: Kernel-based Machine Learning Lab. Kernel-based machine learning methods for classification, regression ... Among other methods kernlab includes Support Vector Machines, Spectral Clustering, Kernel PCA, Gaussian Processes...
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- efficient, flexible and portable. It implements machine learning algorithms under the Gradient Boosting framework. XGBoost...
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- LERS – a system for learning from examples based on rough sets. The paper presents ... choice to use the machine learning approach or the knowledge acquisition approach. In the first...
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- Such structured constraints appear pervasively in machine learning applications, including low-rank matrix completion, sensor...
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- transformation, numerical simulation, statistical modeling, machine learning and much more...
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- software engineering, database and web design, machine learning, and in visual interfaces for other technical...
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- effective for the hyperparameter optimization of machine learning algorithms, scaling better to high dimensions...
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- package OpenML. Exploring Machine Learning Better, Together. ’OpenML.org’ is an online machine learning platform where ... researchers can automatically share data, machine learning tasks and experiments and organize them online...
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- hard MML problems, sometimes assisted by machine learning. It is shown that on the nonarithmetical ... premises are selected by a machine-learning system trained on previous proofs...
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- Joachims [“Making large-scale support vector machine learning practical”, in: B. Schölkopf, C. Burges ... from G. Flake and S. Lawrence [Mach. Learn. 46, 271–290 (2002; Zbl 0998.68107)] yielded ... decomposition method for support vector machines (Tech. Rep.). National Taiwan University (2000)], we show that...