| Issue | #Downvotes for this reason | By |
|---|
| coef0 | Zero coefficient for polynomial and sigmoid kernels Ignored by other kernels | default: null |
| degree | Degree of the polynomial kernel. Ignored by other kernels | default: null |
| gamma | Gamma parameter for the RBF, laplacian, polynomial, exponential chi2 and sigmoid kernels. Interpretation of the default value is left to the kernel; see the documentation for sklearn.metrics.pairwise Ignored by other kernels | default: 0.15000000000000002 |
| kernel | Kernel map to be approximated. A callable should accept two arguments and the keyword arguments passed to this object as kernel_params, and should return a floating point number | default: "laplacian" |
| kernel_params | Additional parameters (keyword arguments) for kernel function passed as callable object | default: null |
| n_components | Number of features to construct How many data points will be used to construct the mapping | default: 9 |
| random_state | If int, random_state is the seed used by the random number generator; If RandomState instance, random_state is the random number generator; If None, the random number generator is the RandomState instance used by `np.random`. | default: null |