Towards an effective cooperation of the user and the computer for classification

Decision trees have been successfully used for the task of classification. However, state-of-the-art algorithms do not incorporate the user in the tree construction process. This paper presents a new user-centered approach to this process where the user and the computer can both contribute their strengths: the user provides domain knowledge and evaluates intermediate results of the algorithm, the computer automatically creates patterns satisfying user constraints and generates appropriate visualizations of these patterns. In this cooperative approach, domain knowledge of the user can direct the search of the algorithm. Additionally, by providing adequate data and knowledge visualizations, the pattern recognition capabilities of the human can be used to increase the effectivity of decision tree construction. Furthermore, the user gets a deeper understanding of the decision tree than just obtaining it as a result of an algorithm. To achieve the intended level of cooperation, we introduc...

• Type: Conference
• Year: 2000
• Where: KDD
• Authors: Mihael Ankerst, Martin Ester, Hans-Peter Kriegel
• Keywords: Data Mining, Decision Tree Construction, Decision Trees, KDD 2000, User