In this video, you learn how to use the SAS Visual Data Mining and Machine Learning feature in SAS Visual Analytics to build a support vector machine model. You also see how to improve the performance of the SVM model by changing properties.
Machine learning – subfield of computer science (more particularly soft computing) that evolved from the study of pattern recognition and computational learning theory in artificial intelligence. In 1959, Arthur defined machine learning as a "Field of study that gives computers the ability to learn without being explicitly programmed".
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While you can't directly link mining hashes with FLOPS, it has been a couple of months since Bitcoin mining passed 10 19 petaflops, or roughly the computing power of all the other computing tasks in the word not allowing for what might go on in .
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Support Vector Machines (SVMs) are supervised learning methods used for classifiion and regression tasks that originated from statistical learning theory . As a classifiion method, SVM is a global classifiion model that generates nonoverlapping partitions and usually employs all attributes.
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