Learning from Data: Unifying Statistics and Computer Science
Cleveland, William S.
Internat. Statist. Rev., Tome 73 (2005) no. 1, p. 217-222 / Harvested from Project Euclid
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Research in the data-oriented areas of computer science is contributing a new wave of theory and tools for learning from data. Some of the research areas complement those in statistics and others overlap. While the research topics of the two fields are not the same, the goals of the research are identical-to enhance theory, methods, models, and systems for the study of data. Unification-close collaboration in research, in teaching, and in applications-would greatly enhance new developments in learning from data.
Publié le : 2005-08-14
Classification:  Data Mining,  Machine Learning,  Data Visualization,  Exploratory Data Analysis,  Computing with Data,  Statistical Model Building 
@article{1123164872,
     author = {Cleveland, William S.},
     title = {Learning from Data: Unifying Statistics and Computer Science},
     journal = {Internat. Statist. Rev.},
     volume = {73},
     number = {1},
     year = {2005},
     pages = { 217-222},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1123164872}
}

Cleveland, William S. Learning from Data: Unifying Statistics and Computer Science. Internat. Statist. Rev., Tome 73 (2005) no. 1, pp.  217-222. http://gdmltest.u-ga.fr/item/1123164872/