Kurzbeschreibung von: Better Decision Tree from Intelligent Instance Selection

This book describes theoretical and experimentalstudies of instance selection to improve data miningmodel. Data preparation is one of the most importantand time consuming phases in knowledge discovery.Preparation tasks often determine the success of datamining engagements. The importance of instanceselection is the primary focus because the size ofcurrent and future databases often exceeds the amountof data which current data mining algorithms canhandle properly. Instance selection thus can be usedto improve scalability of data mining algorithms aswell as improve the quality of the data mining results. This book presents a new optimization-based approachfor instance selection that uses a genetic algorithmto select a subset of instances to produce a simplerdecision tree model with acceptable accuracy. Theresultant trees are easier to comprehend andinterpret by the decision maker and hence more usefulin practice. Numerical results are obtained forseveral difficult test data sets indicating thatGA-based instance selection can often reduce the sizeof the decision tree by an order of magnitude whilestill maintaining good prediction accuracy.