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Data mining is the automated extraction of hidden predictive information from large data sets. To study new algorithms or compare different algorithms, we need a better perspective on a collection of data mining algorithms rather than just their formal definitions. In this research work, I start to create a collection of graphical and interactive implementation of data mining algorithms, called Data Mining Concept Animation Library. Potential users for this library can be future students and instructor of a data mining class. The various types of data mining algorithms that I intend to include in the library are: classification algorithms, regression algorithms, clustering/segmentation algorithms, association algorithms, and sequence analysis algorithms. In this book, I present my work on graphical and interactive implementation of two association algorithms: Apriori algorithm and Frequent Pattern (FP) Growth algorithm. My experience has proved that building the library is not only feasible but worthwhile for teaching and learning key concepts in science and engineering.
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