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