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4Bagging, Boosting, and C4.5
J. Quinlan. AAAI/IAAI, Vol. 1, page 725-730. AAAI Press / The MIT Press, (1996)
6 years ago by @nosebrain
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4Bagging, Boosting, and C4.5
J. Quinlan. AAAI/IAAI, Vol. 1, page 725-730. AAAI Press / The MIT Press, (1996)
6 years ago by @dmir
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lecture:data-mining
comparison
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bagging
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lecture:data-miningcomparisonboostingbaggingc4.5lecture:2014from:nosebrain
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13Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications
R. Agrawal, J. Gehrke, D. Gunopulos, and P. Raghavan. Proceedings of the ACM SIGMOD Int'l Conference on Management of Data, Seattle, Washington, page 94--105. ACM Press, (June 1998)
9 years ago by @nosebrain
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24A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise
M. Ester, H. Kriegel, J. Sander, and X. Xu. Proc. of 2nd International Conference on Knowledge Discovery and, page 226-231. (1996)
10 years ago by @dmir
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24OPTICS: Ordering Points To Identify the Clustering Structure
M. Ankerst, M. Breunig, H. peter Kriegel, and J. Sander. page 49--60. ACM Press, (1999)
10 years ago by @dmir
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13Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications
R. Agrawal, J. Gehrke, D. Gunopulos, and P. Raghavan. Proceedings of the ACM SIGMOD Int'l Conference on Management of Data, Seattle, Washington, page 94--105. ACM Press, (June 1998)
10 years ago by @dmir
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11Mining Frequent Patterns without Candidate Generation
J. Han, J. Pei, and Y. Yin. SIGMOD Conference, page 1-12. ACM, (2000)SIGMOD Record 29(2), June 2000.
10 years ago by @dmir
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11Mining Frequent Patterns without Candidate Generation
J. Han, J. Pei, and Y. Yin. SIGMOD Conference, page 1-12. ACM, (2000)SIGMOD Record 29(2), June 2000.
11 years ago by @nosebrain
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24OPTICS: Ordering Points To Identify the Clustering Structure
M. Ankerst, M. Breunig, H. peter Kriegel, and J. Sander. page 49--60. ACM Press, (1999)
11 years ago by @nosebrain
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24A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise
M. Ester, H. Kriegel, J. Sander, and X. Xu. Proc. of 2nd International Conference on Knowledge Discovery and, page 226-231. (1996)
13 years ago by @nosebrain
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4Bagging, Boosting, and C4.5

4Bagging, Boosting, and C4.5

13Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications

24A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise

24OPTICS: Ordering Points To Identify the Clustering Structure

13Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications

11Mining Frequent Patterns without Candidate Generation

11Mining Frequent Patterns without Candidate Generation

24OPTICS: Ordering Points To Identify the Clustering Structure

24A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise

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