Jezik: | Slovenski jezik |
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Leto izida: | 2020 |
Tipologija: | 2.11 - Diplomsko delo |
Organizacija: | UL FU - Fakulteta za upravo |
Založnik: | [S. Bizjak] |
UDK: | 004.8 |
COBISS: | 58738435 |
Št. ogledov: | 1351 |
Št. prenosov: | 346 |
Ocena: | 0 (0 glasov) |
Metapodatki: |
Sekundarni jezik: | Angleški jezik |
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Sekundarni naslov: | Techniques for combining predictions in machine learning ensembles |
Sekundarni povzetek: | Machine learning of ensembles aims at reducing the predictive error by integrating multiple models into a single one. One of the key components of algorithms for ensemble learning is combining predictions of the base models. In the thesis, we take a closer look at two functions for combining predictions. The first is majority voting, where all the base models contribute equally to the ensemble prediction. The other is performance weighting, where the contribution of a base model to the ensemble prediction is proportional to the model performance. Combination functions are also implemented in R and tested on a selected data set. |
Sekundarne ključne besede: | machine learning;supervised machine learning;classification;homogeneous ensembles;random forest;combining predictions;performance weighting; |
Vrsta dela (COBISS): | Delo diplomskega seminarja/zaključno seminarsko delo/naloga |
Študijski program: | 0 |
Konec prepovedi (OpenAIRE): | 1970-01-01 |
Komentar na gradivo: | Univ. v Ljubljani, Fak. za matematiko in fiziko, Oddelek za matematiko, Matematika - 1. stopnja |
Strani: | 31 str. |
ID: | 12044725 |