collapse_named_lists

Collapse a list of named lists into one list with the same name

Cooperative learning combines the usual squared error loss of predictions with an agreement penalty to encourage the predictions from different data views to agree. By varying the weight of the agreement penalty, we get a continuum of solutions that include the well-known early and late fusion approaches. Cooperative learning chooses the degree of agreement (or fusion) in an adaptive manner, using a validation set or cross-validation to estimate test set prediction error. In the setting of cooperative regularized linear regression, the method combines the lasso penalty with the agreement penalty (Ding, D., Li, S., Narasimhan, B., Tibshirani, R. (2021) <doi:10.1073/pnas.2202113119>).

Balasubramanian Narasimhan

multiview

Cooperative Learning for Multi-View Analysis

Daisy Yi Ding 

Robert J. Tibshirani

Trevor Hastie

Kenneth Tay

James Yang

collapse_named_lists function

<dl><dt>in_list</dt>
<dd>a list of named lists all with same names (not checked for efficiency)</dd></dl>

Arguments

Collapse a list of named lists into one list with the same name — collapse_named_lists

<dl>

<dt>in_list</dt>
<dd>a list of named lists all with same names (not checked for efficiency)</dd>

</dl>

collapse_named_lists: Collapse a list of named lists into one list with the same name

Description

Usage

Value

Arguments