sispca.data

Classes

`Supervision`	Custom data class for variable used as supervision.
`SISPCADataset`	Custom dataset for supervised independent subspace PCA (sisPCA).

class sispca.data.Supervision(target_data, target_type, target_name=None, target_kernel_K=None, target_kernel_Q=None)

Custom data class for variable used as supervision.

Parameters:

target_data (2D tensor or ndarray) – (n_sample, n_dim_target). The target data used as supervision.
target_type (str) – One of [‘continuous’, ‘categorical’, ‘custom’]. The type of the target data. If ‘custom’, the target_kernel should be provided.
target_name (str) – The name of the target data.
target_kernel_K (2D tensor) – (n_sample, n_sample). Optional. The kernel matrix of the target data. Once provided, the target_data will be ignored.
target_kernel_Q (2D tensor) – (n_sample, n_rank). Optional. The decomposed kernel matrix. K = Q @ Q.T. Will be overriden by target_kernel_K if both are provided.

_calc_kernel()

Calculate the kernel matrix of the target data.

Returns:: An object of Kernel. Use the realization() method to get the (n, n) kernel matrix.
Return type:: Kernel

class sispca.data.SISPCADataset(data, target_supervision_list: List[Supervision])

Bases: torch.utils.data.Dataset

Custom dataset for supervised independent subspace PCA (sisPCA).

Parameters:

data (2D tensor) – (n_sample, n_feature). Data to run sisPCA on.
target_supervision_list (list of Supervision) – List of Supervision objects.