glearn.kernels.Kernel.__call__#
- Kernel.__call__()#
Evaluate the kernel function or its derivatives.
- Parameters:
- xfloat or array_like[float]
Input points to the kernel function.
- derivativeint, default=0
The order of the derivative of the kernel function. Zero means no derivative.
- Returns:
- yfloat or numpy.array[float]
The value of the kernel function or its derivatives. The size of
y
is the same as the size of the input argumentx
.
Examples
>>> from glearn import kernels >>> # Create an exponential kernel >>> kernel = kernels.Exponential() >>> # Evaluate kernel at the point x=0.5 >>> x = 0.5 >>> kernel(x) 0.6065306597126334 >>> # Evaluate first derivative of kernel at the point x=0.5 >>> kernel(x, derivarive=1) -0.6065306597126334 >>> # Evaluate second derivative of kernel at the point x=0.5 >>> kernel(x, derivarive=2) 0.6065306597126334