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Data mining is the process of automatically extracting new and
useful knowledge hidden in large datasets. This book focuses on the
enhancement of following three data mining techniques for achieving
the better mining results: Association Rule Mining (ARM),
Clustering Classification In Association Rule Mining (ARM), two
algorithms known as Apriori algorithm and FP-Growth algorithm have
been enhanced for better mining results. An efficient partitional
clustering algorithm utilizing the well-known technique, k-means
clustering is proposed in this book to tackle the problem of empty
clusters. Classification operation usually uses supervised learning
methods that induce a classification model from a database. The
k-Nearest Neighbor (k-NN) is one of the simplest classification
methods used in data mining and machine learning. in this book, the
proposed algorithm improved the performance of conventional k-NN
algorithm by identifying the optimal value of k."
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