Predict the Personality of Facebook Profiles Using Automatic Learning Techniques and BFI Test

2019 ◽  
pp. 482-493 ◽  
Author(s):  
Graciela Guerrero ◽  
Elvis Sarchi ◽  
Freddy Tapia
Keyword(s):  
Automatic Learning ◽  
Learning Techniques

PREDICTION IN HEALTH DOMAIN USING BAYESIAN NETWORKS OPTIMIZATION BASED ON INDUCTION LEARNING TECHNIQUES

2006 ◽  
Vol 17 (03) ◽  
pp. 447-455 ◽  
Author(s):  
PABLO FELGAER ◽  
PAOLA BRITOS ◽  
RAMÓN GARCÍA-MARTÍNEZ
Keyword(s):  
Bayesian Networks ◽  
Bayesian Network ◽  
Hybrid Method ◽  
Learning Process ◽  
Directed Acyclic Graph ◽  
Learning Method ◽  
Automatic Learning ◽  
Acyclic Graph ◽  
Health Domain ◽  
Learning Techniques

A Bayesian network is a directed acyclic graph in which each node represents a variable and each arc a probabilistic dependency; they are used to provide: a compact form to represent the knowledge and flexible methods of reasoning. Obtaining it from data is a learning process that is divided in two steps: structural learning and parametric learning. In this paper we define an automatic learning method that optimizes the Bayesian networks applied to classification, using a hybrid method of learning that combines the advantages of the induction techniques of the decision trees (TDIDT-C4.5) with those of the Bayesian networks. The resulting method is applied to prediction in health domain.

scholarly journals Data analysis and tools applied to modeling and simulation of a PV system in Ecuador

Enfoque UTE ◽  
2018 ◽  
Vol 9 (4) ◽  
pp. 1-12
Author(s):  
Darío Javier Benavides Padilla ◽  
F Jurado ◽  
Luis G González
Keyword(s):  
Computational Simulation ◽  
Photovoltaic System ◽  
Pv System ◽  
Automatic Learning ◽  
Educational Models ◽  
Energy Estimation ◽  
Engineering Studies ◽  
Learning Techniques ◽  
The University ◽  
Made In

This paper presents a research was carried out for the management of a photovoltaic system in a Microgrid, with applications and the use of tools applied to modeling and computational simulation in the Microgrid laboratory implanted in the facilities of the University of Cuenca (Ecuador). Additionally, through the use of automatic learning techniques, the behavior of the photovoltaic system has been modeled in the study area based on radiation and temperature with very good results. In addition, several applications can be made in real engineering studies such as feasibility, performance analysis, energy estimation, educational models, etc.

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