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Abstract: Classification of large datasets is an important data mining problem. Many classification algorithms have been proposed in the literature, but studies have shown that so far no algorithm uniformly outperforms all other algorithms in terms of quality. In this paper, we present a unifying framework for decision tree classifiers that separates the scalability aspects of algorithms for constructing a decision tree from the central features that determine the quality of the tree. This... (Update)
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BibTeX entry: (Update)
J. Gehrke, R. Ramakrishnan, and V. Ganti. Rainforest - A framework for fast decision tree construction of large datasets. VLDB 1996. http://citeseer.ist.psu.edu/gehrke98rainforest.html More
@article{ gehrke00rainforest,
author = "Johannes Gehrke and Raghu Ramakrishnan and Venkatesh Ganti",
title = "RainForest - A Framework for Fast Decision Tree Construction of Large Datasets",
journal = "Data Mining and Knowledge Discovery",
volume = "4",
number = "2/3",
pages = "127-162",
year = "2000",
url = "citeseer.ist.psu.edu/gehrke98rainforest.html" }
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