discretization of the input data. The paper describes a Fast Class-Attribute Interdependence Maximization. (F-CAIM) algorithm that is an extension of the. MCAIM: Modified CAIM Discretization Algorithm for. Classification. Shivani V. Vora. (Research) Scholar. Department of Computer Engineering, SVNIT. CAIM (Class-Attribute Interdependence Maximization) is a discretization algorithm of data for which the classes are known. However, new arising challenges.

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Updated 17 Oct The task of extracting knowledge from databases is quite often performed by machine learning algorithms. The majority of these algorithms can be applied only to data described by discrete numerical or nominal attributes features. In the case of continuous attributes, there is a need for a discretization algorithm that transforms continuous attributes into discrete discretkzation.

This code is based on paper: One can start with “ControlCenter. If there is any problemplease let me know. I will answer you as soon as possible. Hello sir i am student of jntuk university.


Thanks for the code Guangdi Li. I have a question regarding the class labels. I am not able to understand the class labels assigned to the Yeast dataset. Aren’t the class label supposed to be a binary indicator matrix with 1ofK coding?

Could you please send me the data directly? Then I could test it and find the problem. Hi, I got a error, can u help alyorithm Attempted to access B 0 ; index must be a positive integer or logical.

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ur-CAIM: Improved CAIM Discretization for Unbalanced and Balanced Data

xiscretization You are now following this Submission You will see updates in your activity feed You may receive emails, depending on your notification preferences. CAIM class-attribute interdependence maximization is designed to discretize continuous data. Comments and Ratings 4. Hemanth Hemanth view profile.


ur-CAIM: An Improved CAIM Discretization Algorithm for Unbalanced and Balanced Data Sets

Guangdi Li Guangdi Li view profile. Yu Li Yu Li view profile. Updates 17 Oct 1. Tags Add Tags classification data mining discretization.

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