Tags: Algorithms, Books, C4, C5, Classifier System, Classifiers, Data Mining, Databases, Decision Trees, Entropy, Gain Ratio, Internals, Keyword, Linear Classifier, Open Source, Representative Data, Second Half, See5, Unix, Windowing

Despite its age this classic is invaluable to any serious user of See5 (Windows) or C5.0 (UNIX). C4.5 (See5/C5) is a linear classifier system that is often used for machine learning, or as a data mining tool for discovering patterns in databases. The classifiers can be in the form of either decision trees or rule sets. Just like ID3 it employs a “divide and conquer” strategy and uses entropy (information content) to compute its gain ratio (the split criteria).C5.0 and See5 are built on C4.5, which is open source and free. However, since C5.0 and See5 are commercial products the code and the internals of the See5/C5 algorithms are not public. This is why this book is still so valuable. The first half of the book explains how C4.5 works, and describes its features, for example, partitioning, pruning, and windowing in detail. The book also discusses how C4.5 should be used, and potential problems with over-fit and non-representative data. The second half of the book gives a complete













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