# gpflow.kernels.base¶

## gpflow.kernels.base.ReducingCombination¶

class gpflow.kernels.base.ReducingCombination(kernels, name=None)[source]

Bases: gpflow.kernels.base.Combination

Attributes
active_dims
on_separate_dimensions

Checks whether the kernels in the combination act on disjoint subsets of dimensions.

parameters
trainable_parameters

Methods

 __call__(self, X[, X2, full_cov, presliced]) Call self as a function. on_separate_dims(self, other) Checks if the dimensions, over which the kernels are specified, overlap. slice(self, X, X2, NoneType] = None) Slice the correct dimensions for use in the kernel, as indicated by self.active_dims. slice_cov(self, cov) Slice the correct dimensions for use in the kernel, as indicated by self.active_dims for covariance matrices.
 K K_diag
Parameters
• kernels (List[Kernel]) –

• name (Optional[str]) –