def predict(self, Xt):
"""
Make predictions on test data
Parameters
----------
Xt: m x n input test matrix
Returns
-------
m x 1 array of predictions on the test set.
"""
Zt = self._rft / Xt
pred = numpy.dot(Zt, self.model["weights"])
if self.model["multiclass"]:
pred = utils.dummydecode(pred, self.model["zerobased"])
return pred
def predict(self, Xt):
"""
Make Predictions on test data
predict(Xt)
Parameters
----------
Xt: m x n input test matrix
Returns
-------
m x 1 array of predictions on the test set.
"""
kernel = self._kernel
K = kernel.gram(self.model["data"], Xt)
pred = numpy.dot(K, self.model["alpha"])
if self.model["multiclass"]:
pred = utils.dummydecode(pred, self.model["zerobased"])
return pred
