MAKING EFFICIENT LEARNING ALGORITHMS WITH EXPONENTIALLY MANY FEATURES. Logitboost of Simple Bayesian Classifier.
Amplifying the Block Matrix Structure for Spectral Clustering. CURLER: Finding and Visualizing Nonlinear Correlated Clusters. 2005.Īnthony K H Tung and Xin Xu and Beng Chin Ooi. A Regularized Nonsmooth Newton Method for Multi-class Support Vector Machines. Library Release Form Name of Author: Stanley Robson de Medeiros Oliveira Title of Thesis: Data Transformation For Privacy-Preserving Data Mining Degree: Doctor of Philosophy Year this Degree Granted. IEEE Transactions on Information Theory, May 1972, 431-433. (1972) "The Reduced Nearest Neighbor Rule". IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. (1980) "Nosing Around the Neighborhood: A New System Structure and Classification Rule for Recognition in Partially Exposed Environments". (1973) Pattern Classification and Scene Analysis. "The use of multiple measurements in taxonomic problems" Annual Eugenics, 7, Part II, 179-188 (1936) also in "Contributions to Mathematical Statistics" (John Wiley, NY, 1950).ĭuda,R.O., & Hart,P.E. The 38th sample: 4.9,3.6,1.4,0.1,"Iris-setosa" where the errors are in the second and third features.įisher,R.A. The 35th sample should be: 4.9,3.1,1.5,0.2,"Iris-setosa" where the error is in the fourth feature.
This data differs from the data presented in Fishers article (identified by Steve Chadwick, spchadwick ). Predicted attribute: class of iris plant. One class is linearly separable from the other 2 the latter are NOT linearly separable from each other. (See Duda & Hart, for example.) The data set contains 3 classes of 50 instances each, where each class refers to a type of iris plant. Fisher's paper is a classic in the field and is referenced frequently to this day. This is perhaps the best known database to be found in the pattern recognition literature. Click here to try out the new site.ĭownload: Data Folder, Data Set DescriptionĪbstract: Famous database from Fisher, 1936 Check out the beta version of the new UCI Machine Learning Repository we are currently testing! Contact us if you have any issues, questions, or concerns.
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