1 citations · 2 across the 3 of their papers we have counts for
3 papers
Cost-constrained multi-label group feature selection using shadow features
Tomasz Klonecki, Paweł Teisseyre, Jaesung Lee
We consider the problem of feature selection in multi-label classification, considering the costs assigned to groups of features. In this task, the goal is to select a subset of fe…
Verifying the Selected Completely at Random Assumption in Positive-Unlabeled Learning
Paweł Teisseyre, Konrad Furmańczyk, Jan Mielniczuk
The goal of positive-unlabeled (PU) learning is to train a binary classifier on the basis of training data containing positive and unlabeled instances, where unlabeled observations…
Linear regression model selection using p-values when the model dimension grows
Piotr Pokarowski, Jan Mielniczuk, Paweł Teisseyre
We consider a new criterion-based approach to model selection in linear regression. Properties of selection criteria based on p-values of a likelihood ratio statistic are studied f…