Access the full text.
Sign up today, get DeepDyve free for 14 days.
B. Cestnik, I. Kononenko, I. Bratko (1987)
ASSISTANT 86: A Knowledge-Elicitation Tool for Sophisticated Users
J. Quinlan (1987)
Generating Production Rules from Decision Trees
D. Hochbaum (1982)
Approximation Algorithms for the Set Covering and Vertex Cover ProblemsSIAM J. Comput., 11
R. Thisted, D. Phillips, A. Ravindran, J. Solberg (1977)
Operations Research: Principles and Practice.Journal of the American Statistical Association, 72
K. Cios, Ning Liu (1995)
An algorithm which learns multiple covers via integer linear programming. Part I: the CLILP2 algorithmKybernetes, 24
K. Cios, Ning Liu (1995)
An algorithm which learns multiple covers via integer linear programming. Part II: experimental results and conclusionsKybernetes, 24
G. Nemhauser, L. Wolsey (2020)
Integer Programming
J. Quinlan (1992)
C4.5: Programs for Machine Learning
S. Thrun (1991)
The MONK''s Problems-A Performance Comparison of Different Learning Algorithms, CMU-CS-91-197, Sch
G. Torkzadeh, K. Cios, K. Pflughoeft (1996)
Inductive machine learning for instrument developmentInf. Manag., 31
M. Bellmore, H. Ratliff (1971)
Set Covering and Involutory BasesManagement Science, 18
R. Michalski, James Larson (1978)
Selection of Most Representative Training Examples and Incremental Generation of VL1 Hypotheses: The Underlying Methodology and the Description of Programs ESEL and AQ11
V. Chvátal (1979)
A Greedy Heuristic for the Set-Covering ProblemMath. Oper. Res., 4
W. Wolberg, O. Mangasarian (1990)
Multisurface method of pattern separation for medical diagnosis applied to breast cytology.Proceedings of the National Academy of Sciences of the United States of America, 87
W. Wolberg, O. Mangasarian, R. Setiono (1989)
Pattern Recognition Via Linear Programming: Theory and Application to Medical Diagnosis
Xindong Wu (1993)
The HCV induction algorithm
J. Quinlan (1987)
Simplifying decision treesInt. J. Man Mach. Stud., 27
Kristin Bennett, O. Mangasarian (1992)
Robust linear programming discrimination of two linearly inseparable setsOptimization Methods & Software, 1
R. Michalski (1969)
On the Quasi-Minimal Solution of the General Covering Problem
T. Niblett (1987)
Constructing Decision Trees in Noisy Domains
R. Michalski (1990)
Learning flexible concepts: fundamental ideas and a method based on two-tiered representationMachine Learning
Presents an inductive machine learning algorithm called CLIP3 (Cover learning using integer programming). CLIP3 is an extension of the CLILP2 algorithm. CLIP3 generates multiple rules for a given concept from two sets of discrete attribute data. It combines the best concepts of tree‐based and rule‐based algorithms to produce a highly reliable machine‐learning algorithm. The algorithm is run on the benchmark “MONK′s data sets”. Compares the results of standard machine learning algorithms such as the ID and AQ families of algorithms. The algorithm is also run on the breast cancer data set and the results are compared with C4.5 algorithm results.
Kybernetes – Emerald Publishing
Published: Jul 1, 1997
Keywords: Data capture; Data mining; Health care; Linear programming; Machine learning
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.