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Učinkovita implementacija odločitvenega drevesa z logistično regresijo v listih
ID Volk, Martin (Author), ID Kononenko, Igor (Mentor) More about this mentor... This link opens in a new window

URLURL - Presentation file, Visit http://eprints.fri.uni-lj.si/3071/ This link opens in a new window

Abstract
Namen diplomske naloge je bila implementacija algoritma za gradnjo odločitvenih dreves z logistično regresijo v listih. Ker se takšni algoritmi uporabljajo za analizo športnih tekem, kjer je količina podatkov zelo velika, je največja pomanjkljivost takšnih algoritmov poraba pomnilniškega prostora, ki je potreben za gradnjo modela. V nalogi sta na začetku predstavljena algoritem za gradnjo odločitvenih dreves in algoritem za izdelavo modela logistične regresije. Temu sledi opis algoritma za gradnjo dreves z logistično regresijo v listih, na katerem temelji naša rešitev. Na koncu je predstavljena naša implementacija in rezultati testov.

Language:Unknown
Keywords:odločitveno drevo, logistična regresija
Work type:Bachelor thesis/paper
Organization:FRI - Faculty of Computer and Information Science
Year:2015
PID:20.500.12556/RUL-72330 This link opens in a new window
COBISS.SI-ID:1536567491 This link opens in a new window
Publication date in RUL:13.09.2015
Views:1310
Downloads:247
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Secondary language

Language:Unknown
Title:Efficient implementation of decision tree with logistic regression in leaves
Abstract:
The purpose of this thesis was implementation of an algorithm for building decision trees with logistic regression in the leaves. Since such algorithms are used for sport data analysis, where the amount of data to analyse is large, the biggest drawback of these algorithms is the consumption of computer memory required to build the model. First, an algorithm for building decision trees and an algorithm for building logistic regression models are described. This is followed by a description of an algorithm for building decision trees with logistic regression in the leaves, on which our solution is based. At the end our implementation is presented together with results of the tests.

Keywords:decision tree, logistic regression

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