A Streaming Parallel Decision Tree Algorithm
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[1] Imrich Chlamtac,et al. The P2 algorithm for dynamic calculation of quantiles and histograms without storing observations , 1985, CACM.
[2] J. Ross Quinlan,et al. C4.5: Programs for Machine Learning , 1992 .
[3] Alberto Maria Segre,et al. Programs for Machine Learning , 1994 .
[4] Rakesh Agrawal,et al. A One-Pass Space-Efficient Algorithm for Finding Quantiles , 1995, COMAD.
[5] Rakesh Agrawal,et al. SPRINT: A Scalable Parallel Classifier for Data Mining , 1996, VLDB.
[6] Jorma Rissanen,et al. SLIQ: A Fast Scalable Classifier for Data Mining , 1996, EDBT.
[7] Vipin Kumar,et al. ScalParC: a new scalable and efficient parallel classification algorithm for mining large datasets , 1998, Proceedings of the First Merged International Parallel Processing Symposium and Symposium on Parallel and Distributed Processing.
[8] Bruce G. Lindsay,et al. Approximate medians and other quantiles in one pass and with limited memory , 1998, SIGMOD '98.
[9] Sanjay Ranka,et al. CLOUDS: A Decision Tree Classifier for Large Datasets , 1998, KDD.
[10] Girija J. Narlikar,et al. A Parallel, Multithreaded Decision Tree Builder , 1998 .
[11] Catherine Blake,et al. UCI Repository of machine learning databases , 1998 .
[12] Michael Werman,et al. An On-Line Agglomerative Clustering Method for Nonstationary Data , 1999, Neural Computation.
[13] Alok N. Choudhary,et al. Efficient Parallel Classification Using Dimensional Aggregates , 1999, Large-Scale Parallel Data Mining.
[14] Johannes Gehrke,et al. BOAT—optimistic decision tree construction , 1999, SIGMOD '99.
[15] Yishay Mansour,et al. On the Boosting Ability of Top-Down Decision Tree Learning Algorithms , 1999, J. Comput. Syst. Sci..
[16] Sanjay Ranka,et al. Parallel out-of-core divide-and-conquer techniques with application to classification trees , 1999, Proceedings 13th International Parallel Processing Symposium and 10th Symposium on Parallel and Distributed Processing. IPPS/SPDP 1999.
[17] Sanjeev Khanna,et al. Space-efficient online computation of quantile summaries , 2001, SIGMOD '01.
[18] João Gama,et al. Parallel Implementation of Decision Tree Learning Algorithms , 2001, EPIA.
[19] Alípio Mário Jorge,et al. Proceedings of the10th Portuguese Conference on Artificial Intelligence on Progress in Artificial Intelligence, Knowledge Extraction, Multi-agent Systems, Logic Programming and Constraint Solving , 2001 .
[20] S. Muthukrishnan,et al. How to Summarize the Universe: Dynamic Maintenance of Quantiles , 2002, VLDB.
[21] Ruoming Jin,et al. Communication and Memory Efficient Parallel Decision Tree Construction , 2003, SDM.
[22] Yannis E. Ioannidis,et al. The History of Histograms (abridged) , 2003, VLDB.
[23] Vipin Kumar,et al. Parallel Formulations of Decision-Tree Classification Algorithms , 2004, Data Mining and Knowledge Discovery.
[24] Graham Cormode,et al. An improved data stream summary: the count-min sketch and its applications , 2004, J. Algorithms.
[25] Sudipto Guha,et al. Approximation and streaming algorithms for histogram construction problems , 2006, TODS.
[26] Janez Demsar,et al. Statistical Comparisons of Classifiers over Multiple Data Sets , 2006, J. Mach. Learn. Res..
[27] Xuemin Lin,et al. Continuously maintaining order statistics over data streams: extended abstract , 2007 .
[28] Léon Bottou,et al. The Tradeoffs of Large Scale Learning , 2007, NIPS.
[29] Xuemin Lin,et al. Continuously Maintaining Order Statistics over Data Streams , 2007, ADC.
[30] Wei-Yin Loh,et al. Classification and regression trees , 2011, WIREs Data Mining Knowl. Discov..