Prototype Selection and Feature Subset Selection by Estimation of Distribution Algorithms. A Case Study in the Survival of Cirrhotic Patients Treated with TIPS

The Transjugular Intrahepatic Portosystemic Shunt (TIPS) is an interventional treatment for cirrhotic patients with portal hypertension. In the light of our medical staff's experience, the consequences of TIPS are not homogeneous for all the patients and a subgroup dies in the first six months after TIPS placement. An investigation for predicting the conduct of cirrhotic patients treated with TIPS is carried out using a clinical database with 107 cases and 77 attributes. We have applied a new Estimation of Distribution Algorithms based approach in order to perform a Prototype and Feature Subset Selection to improve the classification accuracy obtained using all the variables and all the cases. Used paradigms are K-Nearest Neighbours, Artificial Neural Networks and Classification Trees.

[1]  A Ochs,et al.  The first decade of the transjugular intrahepatic portosystemic shunt (TIPS): state of the art. , 2008, Liver.

[2]  Belur V. Dasarathy,et al.  Nearest neighbor (NN) norms: NN pattern classification techniques , 1991 .

[3]  Ron Kohavi,et al.  Wrappers for Feature Subset Selection , 1997, Artif. Intell..

[4]  H. Mühlenbein,et al.  From Recombination of Genes to the Estimation of Distributions I. Binary Parameters , 1996, PPSN.

[5]  P. Kamath,et al.  A model to predict poor survival in patients undergoing transjugular intrahepatic portosystemic shunts , 2000, Hepatology.

[6]  J. Ross Quinlan,et al.  C4.5: Programs for Machine Learning , 1992 .

[7]  I Inza,et al.  Representing the behaviour of supervised classification learning algorithms by Bayesian networks , 1999, Pattern Recognit. Lett..

[8]  Rm Cameron-Jones,et al.  Instance Selection by Encoding Length Heuristic with Random Mutation Hill Climbing , 1995 .

[9]  Essaid Bouktache,et al.  A Fast Algorithm for the Nearest-Neighbor Classifier , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  J. Krige,et al.  Management of oesophageal varices , 1994, The Lancet.

[11]  Jianping Zhang,et al.  Selecting Typical Instances in Instance-Based Learning , 1992, ML.

[12]  Thomas G. Dietterich Approximate Statistical Tests for Comparing Supervised Classification Learning Algorithms , 1998, Neural Computation.

[13]  M. Stone Cross‐Validatory Choice and Assessment of Statistical Predictions , 1976 .

[14]  Fernando G. Lobo,et al.  A Survey of Optimization by Building and Using Probabilistic Models , 2000, Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334).

[15]  David B. Skalak,et al.  Prototype and Feature Selection by Sampling and Random Mutation Hill Climbing Algorithms , 1994, ICML.

[16]  Thomas G. Dietterich What is machine learning? , 2020, Archives of Disease in Childhood.

[17]  David E. Goldberg,et al.  A Survey of Optimization by Building and Using Probabilistic Models , 2002, Comput. Optim. Appl..

[18]  Dennis L. Wilson,et al.  Asymptotic Properties of Nearest Neighbor Rules Using Edited Data , 1972, IEEE Trans. Syst. Man Cybern..

[19]  Pedro Larrañaga,et al.  Feature Subset Selection by Bayesian network-based optimization , 2000, Artif. Intell..

[20]  Pedro Larrañaga,et al.  Using Bayesian networks in the construction of a bi-level multi-classifier. A case study using intensive care unit patients data , 2001, Artif. Intell. Medicine.

[21]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .