Model selection for learning boolean hypothesis

Model selection for learning boolean hypothesis

The state of the art in machine learning of Boolean functions is to learn a hypothesis h, which is similar to a target hypothesis f, using a training sample of size N and a family of a priori models in a given hypothesis set H, such that h must belong to some model in this family. An important chara...

Full description

Bibliographic Details
Main Author: Castro, Joel Edu Sanchez
Other Authors: Barrera, Junior
Format: Others
Language:en
Published: Biblioteca Digitais de Teses e Dissertações da USP 2018
Subjects:
Aprendizado de máquina
Boolean hypothesis
Dimensão VC
Domain partitions
Hipóteses booleanas
Learning feasibility
Machine learning
Partições do domínio
VC-dimension
Viabilidade de aprendizado
Online Access:http://www.teses.usp.br/teses/disponiveis/45/45134/tde-02042019-231050/

Internet

http://www.teses.usp.br/teses/disponiveis/45/45134/tde-02042019-231050/

Similar Items