Models of logistic regression learners, the default value is If the binary learners are linear classification If the binary learners are SVMs or linearĬlassification models of SVM learners, the default value is The character vectors in BuiltInOptions or a character vectorĭesignating a custom function name. Value - Binary learner loss function, specified as one of That accepts predictor data with 100 observations (in rows) of three predictor variables (inĬolumns), specify these coder attributes of X for the coder configurer You can modify the coder attributes by using dot notation. Tunability - This value must be true, meaning that predict in the generated C/C++ code always includes predictor data as an input. The default data type depends on the data type of the input X. The number of rows, and the second value of SizeVectorĭataType - This value is single or double. That the array has variable-size rows and fixed-size columns. VariableDimensions - The default value is, which indicates that the array size is fixed as specified in To switch the elements of SizeVector (forĮxample, to change to ), modifyĬlassificationECOCCoderConfigurer accordingly. Number of observations and p corresponds to theĬlassificationECOCCoderConfigurer is 'columns', ClassificationECOCCoderConfigurer is 'rows',