Class for learning a logistic regression model that has non-negative coefficients. The first class value is assumed to be the positive class value (i.e. 1.0).
The table below describes the options available for NonNegativeLogisticRegression.
The preferred number of instances to process if batch prediction is being performed. More or fewer instances may be provided, but this gives implementations a chance to specify a preferred batch size.
If set to true, classifier may output additional info to the console.
If set, classifier capabilities are not checked before classifier is built (Use with caution to reduce runtime).
The number of decimal places to be used for the output of numbers in the model.
The number of threads to use, which should be >= size of thread pool.
The size of the thread pool, for example, the number of cores in the CPU.
The random number seed to be used.
The table below describes the capabilities of NonNegativeLogisticRegression.
Binary class, Missing class values
Min # of instances