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Machine learning method that modifies a core of a machine to adjust for a weight and selects a trained machine comprising a sequential minimal optimization (SMO) algorithm
Machine learning method that modifies a core of a machine to adjust for a weight and selects a trained machine comprising a sequential minimal optimization (SMO) algorithm
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机译:机器学习方法,可修改机器的核心以调整重量并选择包含顺序最小优化(SMO)算法的训练有素的机器
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摘要
Methods for training machines to categorize data, and/or recognize patterns in data, and machines and systems so trained. More specifically, variations of the invention relates to methods for training machines that include providing one or more training data samples encompassing one or more data classes, identifying patterns in the one or more training data samples, providing one or more data samples representing one or more unknown classes of data, identifying patterns in the one or more of the data samples of unknown class(es), and predicting one or more classes to which the data samples of unknown class(es) belong by comparing patterns identified in said one or more data samples of unknown class with patterns identified in said one or more training data samples. Also provided are tools, systems, and devices, such as support vector machines (SVMs) and other methods and features, software implementing the methods and features, and computers or other processing devices incorporating and/or running the software, where the methods and features, software, and processors utilize specialized methods to analyze data.
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