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Statlog (Heart) Data Set

Below are papers that cite this data set, with context shown. Papers were automatically harvested and associated with this data set, in collaboration with Rexa.info.

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Gavin Brown. Diversity in Neural Network Ensembles. The University of Birmingham. 2004.

from the UCI repository (699 patterns), and the Heart disease dataset from Statlog (270 patterns). An ensemble consisting of two networks, each with five hidden nodes, was trained using NC. We use 5-fold cross-validation, and 40 trials from uniform random weights in


Igor Kononenko and Edvard Simec and Marko Robnik-Sikonja. Overcoming the Myopia of Inductive Learning Algorithms with RELIEFF. Appl. Intell, 7. 1997.

Milan Soklic for LYMP, Gail Gong for HEPA, Padhraic Smyth for BOOL and LED, Saso Dzeroski for KRK1 and MESH, Bob Henery for the DIAB, HEART and SAT data sets from the StatLog database at Strathclyde University, and Patrick Murphy and David Aha for the data sets from the Irvine database. We are grateful to our colleagues Saso Dzeroski, Matevz Kovacic,


Elena Smirnova and Ida G. Sprinkhuizen-Kuyper and I. Nalbantis and b. ERIM and Universiteit Rotterdam. Unanimous Voting using Support Vector Machines. IKAT, Universiteit Maastricht.

the hypothesis space H contains the target hyperplane, the hyperplane is consistent with the training data; i.e., it belongs to the version space [7, 11]. Thus, the unanimous-voting classification Data Set Parameters Cvssvm Avssvm Asvm I Heart Statlog P, E=2.0, C=1730 56.3% 100% 73.0% 0.42 Heart-Statlog RBF, G=0.2 , C=2182 40.7% 100% 73.7 % 0.24 Hepatitis P, E=1.4, C=11.7 80.0% 100% 80.0 % 0.72


Alexander K. Seewald. Dissertation Towards Understanding Stacking Studies of a General Ensemble Learning Scheme ausgefuhrt zum Zwecke der Erlangung des akademischen Grades eines Doktors der technischen Naturwissenschaften.

heart h Compressed glyph visualization for dataset heart statlog Compressed glyph visualization for dataset hepatitis Figure 8.6: Glyph visualization for datasets audiology to hepatitis. 79 Compressed glyph visualization for dataset ionosphere


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