Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
On algorithm for building of optimal α-decision trees
RSCTC'10 Proceedings of the 7th international conference on Rough sets and current trends in computing
On optimization of decision trees
Transactions on Rough Sets IV
Dynamic Programming Approach for Partial Decision Rule Optimization
Fundamenta Informaticae - Concurrency Specification and Programming (CS&P)
Relationships between Average Depth and Number of Misclassifications for Decision Trees
Fundamenta Informaticae - Dedicated to the Memory of Professor Manfred Kudlek
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This paper describes a new tool for the study of relationships between depth and number of misclassifications for decision trees. In addition to the algorithm the paper also presents the results of experiments with three datasets from UCI Machine Learning Repository [3].