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This book consists of three (3) Chapters. The first chapter of the concept of Data Mining. This chapter contains the definitions and characteristics of data mining. The second chapter is algorithms of Classification, estimation and prediction. The Algorithm involved are Logistic regression, Naive Bayes, Support Vector Machine, decision tree, K-NN and ANN. The third chapter on Clustering Algorithm and Associations. The algorithm is described in this chapters are K-Means and Apriori algorithm respectively. Interestingly this book explain every algorithm detailly with the example of a systematic…mehr

Produktbeschreibung
This book consists of three (3) Chapters. The first chapter of the concept of Data Mining. This chapter contains the definitions and characteristics of data mining. The second chapter is algorithms of Classification, estimation and prediction. The Algorithm involved are Logistic regression, Naive Bayes, Support Vector Machine, decision tree, K-NN and ANN. The third chapter on Clustering Algorithm and Associations. The algorithm is described in this chapters are K-Means and Apriori algorithm respectively. Interestingly this book explain every algorithm detailly with the example of a systematic comparison between manual and software process (Rapid Miner).
Autorenporträt
Imam Tahyudin is a Lecturer in STMIK AMIKOM Purwokerto, Central Java, Indonesia. He has published some books which were Business Mathematics (2011), Basic statistics (2011), 3 Hours To be Master of Microsoft Office 2010 (2012), Computer Application Using Office 2010 (2012), Discrete Mathematics (2013), DSS and Data Mining (2014).