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This object implements a coach for undertaking epsilon-insensitive aid vector regression. It is executed using the SMO algorithm, letting the usage of non-linear kernels. In case you are interested in performing support vector regression using a linear kernel and you've got a good deal of coaching information then you ought to use the svr_linear_trainer which is extremely optimized for this case.
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This object is a tool for distributing the operate involved in solving a structural_svm_problem throughout numerous personal computers.
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The precedence desk decides the order of binding in chained expressions, when It's not at all expressly specified by parentheses.
This item is usually a tool for Discovering to carry out sequence labeling based upon click to find out more a set of training knowledge. The schooling method makes a sequence_labeler item which may be use to forecast the labels of recent data sequences.
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This object represents a More about the author polynomial kernel for use with kernel Understanding devices that work on sparse vectors.
Trains a nu aid vector device for solving binary classification complications and outputs a decision_function. It can be applied utilizing the SMO algorithm. The implementation from the nu-svm coaching algorithm employed by this library is based on the next excellent papers: