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Towards an effective cooperation of the user and the computer for classification

Published: 01 August 2000 Publication History
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References

[1]
Ankerst M., Elsen C., Ester M., Kriegel H.-P.: Visual Classification: An Interactive Approach to Decision Tree Construction, Proc. 5th Int. Conf. on Knowledge Discovery and Data Mining (KDD'99), San Diego, CA, 1999, pp. 392-396.
[2]
Ankerst M., Keim D. A., Kriegel H.-P.:"Circle Segments: A Technique for Visually Exploring Large Multidimensional Data Sets, Proc. Visualization '96, Hot Topic Session, San Francisco, CA, 1996.
[3]
http://www.angoss.com/
[4]
Breiman L., Friedman J.H., Olshen R.A., Stone P.J.: Classification and Reggression Trees, Wadsworth Publishing, Belmont, CA, 1984.
[5]
Berchtold S., Jagadish H.V., Ross K.A.: Independence Diagrams: A Technique for Visual Data Mining, Proc. 4th Intl. Conf. on Knowledge Discovery and Data Mining (KDD'98), New York City, 1998, pp. 139-143.
[6]
Domingos P.: The Role of Occam's Razor in Knowledge Discovery, Data Mining and Knowledge Discovery, an International Journal, Kluwer Academic Publishers, Vol.3, 1999, pp. 409-425.
[7]
Coppersmith D., Hong S.J., Hosking J.R.M.: Partitioning Nominal Attributes in Decision Trees, Data Mining and Knowledge Discovery, an International Journal, Kluwer Academic Publishers, Vol.3, 1999, pp. 197-217.
[8]
Han J., Lakshmanan L., Ng R.: Constraint-Based, Multidimensional Data Mining, IEEE Computer, Vol. 32, No. 8, 1999, pp. 46-50.
[9]
Keim D. A.:Visual Database Exploration Techniques, Proc. Tutorial Int. Conf. on Knowledge Discovery & Data Mining (KDD'97), Newport Beach, CA, 1997.(http://www.informatik. uni-halle.de/~keim/PS/KDD97.pdf)
[10]
Kohavi R., Sommerfield D.: Targeting Business Users with Decision Table Classifiers, Proc. 4th Intl. Conf. on Knowledge Discovery and Data Mining (KDD'98), New York City, 1998, pp. 249-253.
[11]
Mehta M., Agrawal R., Rissanen J.: SLIQ: A Fast Scalable Classifier for Data Mining, Proc. of the Int. Conf. on Extending Database Technology (EDBT '96), Avignon, France, 1996.
[12]
Mitchel T.M.: Machine Learning, McGraw Hill, 1997.
[13]
Michie D., Spiegelhalter D.J., Taylor C.C.: Machine Learning, Neural and Statistical Classification, Ellis Horwood, 1994. See also http://www.ncc.up.pt/liacc/ML/statlog/datasets.html.
[14]
NASA Ames Research Center: Introduction to IND Version 2.1, 1992.
[15]
Ridgeway G., Madigan D., Richardson T., O'Kane J.: Interpretable Boosted Naive Bayes Classification, Proc. 4th Intl. Conf. on Knowledge Discovery and Data Mining (KDD'98), New York City, 1998, pp. 101-106.
[16]
http://www.spss.com/answertree/

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cover image ACM Conferences
KDD '00: Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
August 2000
537 pages
ISBN:1581132336
DOI:10.1145/347090
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Published: 01 August 2000

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  • (2023)Integrating scientific knowledge into machine learning using interactive decision treesComputers & Geosciences10.1016/j.cageo.2022.105248170:COnline publication date: 1-Jan-2023
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