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The ID3 algorithm begins with the original set as the root node. On each iteration of the algorithm, it iterates through every unused attribute of the set and calculates the entropy or the information gain of that attribute. It then selects the attribute which has the smallest entropy (or largest information gain) value.
scikit-learn (a free and open-source machine learning library for the Python programming language). Weka (a free and open-source data-mining suite, contains many decision tree algorithms), Notable commercial software: MATLAB, Microsoft SQL Server, and; RapidMiner, SAS Enterprise Miner, IBM SPSS Modeler,
C4.5 is an algorithm used to generate a decision tree developed by Ross Quinlan. [1] C4.5 is an extension of Quinlan's earlier ID3 algorithm.The decision trees generated by C4.5 can be used for classification, and for this reason, C4.5 is often referred to as a statistical classifier.
C5.0, which Quinlan is commercially selling (single-threaded version is distributed under the terms of the GNU General Public License), is an improvement on C4.5.The advantages are speed (several orders of magnitude faster), memory efficiency, smaller decision trees, boosting (more accuracy), ability to weight different attributes, and winnowing (reducing noise).
The CN2 induction algorithm is a learning algorithm for rule induction. [1] It is designed to work even when the training data is imperfect. It is based on ideas from the AQ algorithm and the ID3 algorithm. As a consequence it creates a rule set like that created by AQ but is able to handle noisy data like ID3.
The concept of information gain function falls under the C4.5 algorithm for generating the decision trees and selecting the optimal split for a decision tree node. [1] Some of its advantages include: It can work with both continuous and discrete variables.
Data mining in general and rule induction in detail are trying to create algorithms without human programming but with analyzing existing data structures. [ 1 ] : 415- In the easiest case, a rule is expressed with “if-then statements” and was created with the ID3 algorithm for decision tree learning.
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