evaluations(ty, pv) -> (ACC, MSE, SCC) Calculate accuracy, mean squared error and squared correlation coefficient using the true values

toPyModel(model_ptr) -> model Convert a ctypes POINTER(model) to a Python model

Return a :class:`LearnerModel`. *data_file_name* is the file path of the LIBSVM-format data. *learner_opts* is a :class:`str`. Refer to

Interface functions

transpose matrix X from row format to column format

constructor of :class:`LearnerModel`.

label: label name, start: begin of each class, count: #data of classes, perm: indices to the original data perm, length l, must be allocated before ca

Load the contents from a :class:`TextModel` directory.

The maximum index of xi should be less or equal to the weight vector size.

Set the options to the specific values.

Return the label and a :class:`c_double` array of decision values of the test instance *xi* using :class:`LearnerModel` *m*. *xi* can be

read in a problem (in libsvm format)

read in a problem (in libsvm format)

Set the options to some values (``'-D 1 -T 0 -I 0 -N 1'``).