Učenje optimalne odločitve s klasifikacijskimi drevesi

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Ključne besede

Podatki

Jezik:	Slovenski jezik
Leto izida:	2009
Tipologija:	2.11 - Diplomsko delo
Organizacija:	UL FRI - Fakulteta za računalništvo in informatiko
Založnik:	[M. Zorc]
UDK:	004(043.2)
COBISS:	7149396
Št. ogledov:	141
Št. prenosov:	7
Ocena:	0 (0 glasov)
Metapodatki:

Ostali podatki

Sekundarni jezik:	Angleški jezik
Sekundarni naslov:	[Learning optimal decisions with classification trees]
Sekundarni povzetek:	Learning classification and regression models is one of the most important subfields of machine learning. Classification and regression models are constructed from learning set and used to classify new examples. In practice, we would often need model, which proposes optimal decision, for instance the best therapy for a certain type of illness for a particular patient. The main aim of the diploma thesis is to adapt the algorithm for the construction of classification trees to construct trees that would not predict the outcome but rather the decision leading to the desired outcome. Besides that, we had to develop the methods for measuring the quality of such models, and use it to test them on synthetic and real-world data sets.
Sekundarne ključne besede:	machine learning;classification tree;attribute selection measure;optimal therapy;computer science;diploma;
Vrsta datoteke:	application/pdf
Vrsta dela (COBISS):	Diplomsko delo
Komentar na gradivo:	Univerza v Ljubljani, Fakulteta za računalništvo in informatiko
Strani:	39 str.
ID:	23868200