Non-binary classification trees

1996 ◽  
Vol 6 (3) ◽  
pp. 231-243 ◽  
Author(s):  
Stanislav Keprta
Keyword(s):  
Binary Classification ◽  
Classification Trees

New Glaucoma Classification Method Based on Standard Heidelberg Retina Tomograph Parameters by Bagging Classification Trees

2003 ◽  
Vol 12 (4) ◽  
pp. 340-346 ◽  
Author(s):  
Christian Y. Mardin ◽  
Torsten Hothorn ◽  
Andrea Peters ◽  
Anselm G. J??nemann ◽  
Nhung X. Nguyen ◽  
...  
Keyword(s):  
Classification Trees ◽  
Classification Method ◽  
Heidelberg Retina Tomograph

Identifying Analogue Fields in PCP Applications Using Classification Trees

2018 ◽  
Author(s):  
John Sheldon ◽  
Francisco Alhanati ◽  
Paul Skoczylas
Keyword(s):  
Classification Trees

USING CLASSIFICATION TREES FOR SOFTWARE QUALITY MODELS: LESSONS LEARNED

1999 ◽  
Vol 09 (02) ◽  
pp. 217-231 ◽  
Author(s):  
TAGHI M. KHOSHGOFTAAR ◽  
EDWARD B. ALLEN ◽  
ARCHANA NAIK ◽  
WENDELL D. JONES ◽  
JOHN P. HUDEPOHL
Keyword(s):  
Software Quality ◽  
Classification Trees ◽  
Lessons Learned ◽  
Quality Models ◽  
Model Based ◽  
Software Product ◽  
High Assurance ◽  
Process Metrics ◽  
Product And Process ◽  
Software Quality Models

High software reliability is an important attribute of high-assurance systems. Software quality models yield timely predictions of quality indicators on a module-by-module basis, enabling one to focus on finding faults early in development. This paper introduces the Classification And Regression Trees (CART) a algorithm to practitioners in high-assurance systems engineering. This paper presents practical lessons learned on building classification trees for software quality modeling, including an innovative way to control the balance between misclassification rates. A case study of a very large telecommunications system used CART to build software quality models. The models predicted whether or not modules would have faults discovered by customers, based on various sets of software product and process metrics as independent variables. We found that a model based on two software product metrics had comparable accuracy to a model based on forty product and process metrics.

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