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Silabus

Introduction
Data. Object data and attributes, Nominal attributes, Binary attributes, Ordinal attributes, Numeric attributes, Discrete versus Continuous attributes
Data preprocessing. Data cleaning, data reduction, data transformation, discretization.
Exploration data. Description of data statistics, visualization
Classification. Basic concept, Decision tree, Evaluation of classification model
Advanced Classification. Rule-based classifier, Nearest-neighbor classifier, Bayesian classifier, Artificial neural network
Association rule mining. The basic concept, mining frequent itemset, mining association rule
Sequential pattern mining. Basic concept, mining sequential pattern
Clustering. Clustering analysis, partition clustering method, hierarchical clustering method, density-based clustering method, clustering evaluation
Application of data mining on the document (Text mining). Data collection, preprocessing, feature extraction, modeling


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