KernelCenterer
¶
-
class
ibex.sklearn.preprocessing.
KernelCenterer
¶ Bases:
sklearn.preprocessing.data.KernelCenterer
,ibex._base.FrameMixin
Note
The documentation following is of the class wrapped by this class. There are some changes, in particular:
- A parameter
X
denotes apandas.DataFrame
. - A parameter
y
denotes apandas.Series
.
Center a kernel matrix
Let K(x, z) be a kernel defined by phi(x)^T phi(z), where phi is a function mapping x to a Hilbert space. KernelCenterer centers (i.e., normalize to have zero mean) the data without explicitly computing phi(x). It is equivalent to centering phi(x) with sklearn.preprocessing.StandardScaler(with_std=False).
Read more in the User Guide.
-
fit
(K, y=None)[source]¶ Note
The documentation following is of the class wrapped by this class. There are some changes, in particular:
- A parameter
X
denotes apandas.DataFrame
. - A parameter
y
denotes apandas.Series
.
Fit KernelCenterer
- K : numpy array of shape [n_samples, n_samples]
- Kernel matrix.
self : returns an instance of self.
- A parameter
-
fit_transform
(X, y=None, **fit_params)¶ Note
The documentation following is of the class wrapped by this class. There are some changes, in particular:
- A parameter
X
denotes apandas.DataFrame
. - A parameter
y
denotes apandas.Series
.
Fit to data, then transform it.
Fits transformer to X and y with optional parameters fit_params and returns a transformed version of X.
- X : numpy array of shape [n_samples, n_features]
- Training set.
- y : numpy array of shape [n_samples]
- Target values.
- X_new : numpy array of shape [n_samples, n_features_new]
- Transformed array.
- A parameter
-
transform
(K, y='deprecated', copy=True)[source]¶ Note
The documentation following is of the class wrapped by this class. There are some changes, in particular:
- A parameter
X
denotes apandas.DataFrame
. - A parameter
y
denotes apandas.Series
.
Center kernel matrix.
- K : numpy array of shape [n_samples1, n_samples2]
- Kernel matrix.
- y : (ignored)
Deprecated since version 0.19: This parameter will be removed in 0.21.
- copy : boolean, optional, default True
- Set to False to perform inplace computation.
K_new : numpy array of shape [n_samples1, n_samples2]
- A parameter
- A parameter