| Issue | #Downvotes for this reason | By |
|---|
| alpha | Hyperparameter of the ridge regression that learns the inverse transform (when fit_inverse_transform=True) | default: 1.0 |
| coef0 | Independent term in poly and sigmoid kernels Ignored by other kernels | default: 1 |
| copy_X | If True, input X is copied and stored by the model in the `X_fit_` attribute. If no further changes will be done to X, setting `copy_X=False` saves memory by storing a reference .. versionadded:: 0.18 | default: true |
| degree | Degree for poly kernels. Ignored by other kernels | default: 3 |
| eigen_solver | Select eigensolver to use. If n_components is much less than the number of training samples, arpack may be more efficient than the dense eigensolver | default: "auto" |
| fit_inverse_transform | Learn the inverse transform for non-precomputed kernels (i.e. learn to find the pre-image of a point) | default: false |
| gamma | Kernel coefficient for rbf and poly kernels. Ignored by other kernels | default: null |
| kernel | default: "rbf" | |
| kernel_params | Parameters (keyword arguments) and values for kernel passed as callable object. Ignored by other kernels | default: null |
| max_iter | Maximum number of iterations for arpack If None, optimal value will be chosen by arpack | default: null |
| n_components | Number of components. If None, all non-zero components are kept kernel : "linear" | "poly" | "rbf" | "sigmoid" | "cosine" | "precomputed" Kernel. Default="linear" | default: null |
| n_jobs | The number of parallel jobs to run If `-1`, then the number of jobs is set to the number of CPU cores .. versionadded:: 0.18 | default: -1 |
| random_state | A pseudo random number generator used for the initialization of the residuals when eigen_solver == 'arpack' .. versionadded:: 0.18 | default: null |
| remove_zero_eig | If True, then all components with zero eigenvalues are removed, so that the number of components in the output may be < n_components (and sometimes even zero due to numerical instability) When n_components is None, this parameter is ignored and components with zero eigenvalues are removed regardless | default: false |
| tol | Convergence tolerance for arpack If 0, optimal value will be chosen by arpack | default: 0 |