Predictive Models

LinearCPMModel

Linear Connectome-based Predictive Modeling (CPM) implementation.

This class implements a linear CPM model, allowing for fitting and prediction based on connectome data, covariates, and residuals.

Attributes:

Name	Type	Description
models	ModelDict	A dictionary containing the fitted models for different networks and data types (connectome, covariates, residuals, and full model).
models_residuals	dict	A dictionary storing linear regression models used to calculate residuals for connectome data, controlling for covariates.
edges	dict	A dictionary defining the edges (features) used for each network (e.g., 'positive', 'negative').

Parameters:

Name	Type	Description	Default
edges	dict	Dictionary containing indices of edges for 'positive' and 'negative' networks.	required

__init__(edges)

Initialize the LinearCPMModel.

Parameters:

Name	Type	Description	Default
edges	dict	Dictionary containing indices of edges for 'positive' and 'negative' networks.	required

fit(X, y, covariates)

Fit the CPM model.

This method fits multiple linear regression models for the connectome, covariates, residuals, and full model using the provided data.

Parameters:

Name	Type	Description	Default
X	ndarray	A 2D array of shape (n_samples, n_features) representing the connectome data.	required
y	ndarray	A 1D array of shape (n_samples,) representing the target variable.	required
covariates	ndarray	A 2D array of shape (n_samples, n_covariates) representing the covariates.	required

Returns:

Type	Description
LinearCPMModel	The fitted CPM model instance.

predict(X, covariates)

Predict using the fitted CPM model.

This method generates predictions for the target variable using the connectome, covariates, residuals, and full models.

Parameters:

Name	Type	Description	Default
X	ndarray	A 2D array of shape (n_samples, n_features) representing the connectome data.	required
covariates	ndarray	A 2D array of shape (n_samples, n_covariates) representing the covariates.	required

Returns:

Type	Description
ModelDict	A dictionary containing predictions for each network and model type (connectome, covariates, residuals, and full model).