Finding approximate solutions to combinatorial problems with very large data sets using BIRCH

DOI10.1016/j.csda.2008.08.001zbMath1464.62086OpenAlexW1986114210MaRDI QIDQ962302

Justin Harrington, Matías Salibián Barrera

Publication date: 6 April 2010

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2008.08.001

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Robustness and adaptive procedures (parametric inference) (62F35)

Related Items (3)

Special issue on variable selection and robust procedures ⋮ Editorial: Second special issue on statistical algorithms and software ⋮ Using balanced iterative reducing and clustering hierarchies to compute approximate rank statistics on massive datasets

Cites Work

• Linear grouping using orthogonal regression
• Least Median of Squares Regression
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