A Wrapper Evolutionary Approach for Supervised Multivariate Discretization: A Case Study on Decision Trees

2016 ◽  
pp. 47-58
Author(s):  
Sergio Ramírez-Gallego ◽  
Salvador García ◽  
José Manuel Benítez ◽  
Francisco Herrera
Keyword(s):  
Decision Trees ◽  
Evolutionary Approach ◽  
Multivariate Discretization

EVOLUTIONARY APPROACH IN PROCESS IMPROVEMENT — A CASE STUDY IN AUTO ELECTRICAL ALTERNATOR MANUFACTURING

2012 ◽  
Vol 11 (01) ◽  
pp. 27-50 ◽  
Author(s):  
A. J. JEGADHEESON ◽  
L. KARUNAMOORTHY ◽  
N. ARUNKUMAR ◽  
A. BALAJI ◽  
M. RAJKAMAL
Keyword(s):  
Process Improvement ◽  
Manufacturing Process ◽  
Welding Process ◽  
Evolutionary Approach ◽  
Geometrical Analysis ◽  
Designed Experiments ◽  
Self Development ◽  
Riveting Process

Evolution is "understanding and overcoming current constraints in small steps toward optimum." "Understanding" requires elucidation of facts and corroborating theories that can explain those facts in a coherent manner. "Overcoming" requires self-development to suit the environment. In this paper, a case study about how a manufacturing process is improved in terms of productivity and quality using evolutionary improvements is explained. Here "Understanding" is achieved through use of Shainin Technique, PM analysis, Affinity Diagram, and the engineer's ingenuity, along with Relations diagram. "Overcoming" is achieved through Geometrical Analysis and Designed Experiments. The Study has set a new benchmark in the Stator riveting process by proving it can yield the desired results, and the need to adapt welding process is avoided.

Combining decision trees classifiers: a case study of automatic sleep stage scoring

2012 ◽  
Vol 2 (1) ◽  
pp. 60 ◽  
Author(s):  
Natheer Khasawneh ◽  
Stefan Conrad ◽  
Luay Fraiwan ◽  
Eyad Taqieddin ◽  
Basheer Khasawneh
Keyword(s):  
Decision Trees ◽  
Sleep Stage ◽  
Sleep Stage Scoring

scholarly journals Decision-making on Implementation of IPO Under Topological Uncertainty

2015 ◽  
Vol 63 (1) ◽  
pp. 193-200 ◽  
Author(s):  
Karel Doubravský ◽  
Tomáš Meluzín ◽  
Mirko Dohnal
Keyword(s):  
Decision Making ◽  
Decision Trees ◽  
Initial Public Offering ◽  
Decision Makers ◽  
Structure Topology ◽  
Complex Decision Making ◽  
Flexible Integration ◽  
Complex Decision ◽  
Public Offering

IPO (Initial Public Offering) is a complex decision making task which is always associated with different types of uncertainty. Poor accuracies of available probabilities of lotteries e.g. quantification of investor interest is studied in the first part of this paper (Meluzín, Doubravský, Dohnal, 2012). However, IPO is often prohibitively ill-known. This paper takes into consideration the fact that decision makers cannot specify the structure/topology of the relevant decision tree. It means that one IPO task is specified by several (partially) different decision trees which comes from different sources e.g. from different teams of decision makers/experts. A flexible integration of those trees is based on fuzzy logic using the reconciliation (Meluzín, Doubravský, Dohnal, 2012). The developed algorithm is demonstrated by a case study which is presented in details. The IPO case integrates two partially different decision trees.

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