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Found 4 papers, 0 papers with code
Imputation of missing values in multi-view data
This leads to very large quantities of missing data which, especially when combined with high-dimensionality, makes the application of conditional imputation methods computationally infeasible.
Analyzing hierarchical multi-view MRI data with StaPLR: An application to Alzheimer's disease classification
We introduce an extension of this method to a setting where the data has a hierarchical multi-view structure.
View selection in multi-view stacking: Choosing the meta-learner
The remaining four meta-learners, namely nonnegative ridge regression, nonnegative forward selection, stability selection and the interpolating predictor, show little advantages in order to be preferred over the other three.
Stacked Penalized Logistic Regression for Selecting Views in Multi-View Learning
We compare the performance of StaPLR with an existing view selection method called the group lasso and observe that, in terms of view selection, StaPLR is often more conservative and has a consistently lower false positive rate.
