
mgr inż. Karol Draszawka
Media społecznościowe
Kontakt
- kardrasz@pg.edu.pl
Asystent
- Miejsce pracy
-
Budynek A Elektroniki
pokój EA 521 otwiera się w nowej karcie - Telefon
- (58) 348 61 62
- kadr@eti.pg.edu.pl
Wybrane publikacje
-
Thresholding Strategies for Large Scale Multi-Label Text Classifier
This article presents an overview of thresholding methods for labeling objects given a list of candidate classes’ scores. These methods are essential to multi-label classification tasks, especially when there are a lot of classes which are organized in a hierarchy. Presented techniques are evaluated using the state-of-the-art dedicated classifier on medium scale text corpora extracted from Wikipedia. Obtained results show that the...
-
External Validation Measures for Nested Clustering of Text Documents
Abstract. This article handles the problem of validating the results of nested (as opposed to "flat") clusterings. It shows that standard external validation indices used for partitioning clustering validation, like Rand statistics, Hubert Γ statistic or F-measure are not applicable in nested clustering cases. Additionally to the work, where F-measure was adopted to hierarchical classification as hF-measure, here some methods to...
-
Improving css-KNN Classification Performance by Shifts in Training Data
This paper presents a new approach to improve the performance of a css-k-NN classifier for categorization of text documents. The css-k-NN classifier (i.e., a threshold-based variation of a standard k-NN classifier we proposed in [1]) is a lazy-learning instance-based classifier. It does not have parameters associated with features and/or classes of objects, that would be optimized during off-line learning. In this paper we propose...
wyświetlono 397 razy