Local induction of decision trees: Towards interactive data mining

Conference · Tue Dec 31 04:00:00 EST 1996

OSTI ID:421249

Fulton, T; Kasif, S; Salzberg, S ^[1]; Waltz, D ^[2]

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1. Johns Hopkins Univ., Baltimore, MD (United States)
2. NEC Research Inst., Princeton, NJ (United States)

Decision trees are an important data mining tool with many applications. Like many classification techniques, decision trees process the entire data base in order to produce a generalization of the data that can be used subsequently for classification. Large, complex data bases are not always amenable to such a global approach to generalization. This paper explores several methods for extracting data that is local to a query point, and then using the local data to build generalizations. These adoptively constructed neighborhoods can provide additional information about the query point. Three new algorithms are presented, and experiments using these algorithms are described.

• OSTI ID: 421249
• Report Number(s): CONF-960830--
• Country of Publication: United States
• Language: English

Related Subjects

99 GENERAL AND MISCELLANEOUS
ALGORITHMS
ARTIFICIAL INTELLIGENCE
DATA BASE MANAGEMENT
DECISION TREE ANALYSIS
INFORMATION RETRIEVAL
KNOWLEDGE BASE