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class02 - CAP 4770 Introduction to Data Mining Fall 2008 Dr...

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CAP 4770: Introduction to Data Mining Fall 2008 Dr. Tao Li Florida International University
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CAP 4770 2 Outline Course Logistics Data Mining Introduction Four Key Characteristics Combination of Theory and Application Engineering Process Engineering Process Collection of Functionalities Interdisciplinary field How do we categorize data mining systems? History of Data Mining Research Issues
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CAP 4770 3 adapted from: U. Fayyad, et al. (1995), “From Knowledge Discovery to Data Mining: An Overview,” Advances in Knowledge Discovery and Data Mining, U. Fayyad et al. (Eds.), AAAI/MIT Press Data Target Data Selection Knowledge Preprocessed Data Patterns Mining Algorithms Interpretation/ Evaluation Data Mining: An Engineering Process Preprocessing Data mining: interactive and iterative process.
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CAP 4770 4 Steps of a KDD Process Learning the application domain relevant prior knowledge and goals of application Creating a target data set: data selection Data cleaning and preprocessing: (may take 60% of effort!) Data reduction and transformation Find useful features, dimensionality/variable reduction, invariant representation. Choosing functions of data mining summarization, classification, regression, association, clustering. Choosing the mining algorithm(s) Data mining : search for patterns of interest Pattern evaluation and knowledge presentation visualization, transformation, removing redundant patterns, etc. Use of discovered knowledge
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CAP 4770 5 Outline Course Logistics Data Mining Introduction Four Key Characteristics Combination of Theory and Application Engineering Process Collection of Functionalities Collection of Functionalities Interdisciplinary field How do we categorize data mining systems? History of Data Mining Research Issues Curse of Dimensionality
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CAP 4770 6 Architecture of a Typical Data Mining System Data Warehouse Data cleaning & data integration Filtering Databases Database or data  warehouse server Data mining engine Pattern evaluation Graphical user interface Knowledge-base
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CAP 4770 7 Data Mining: On What Kind of Data? Relational databases Data warehouses Transactional databases Advanced DB and information repositories Object-oriented and object-relational databases Spatial databases Time-series data and temporal data Text databases and multimedia databases Heterogeneous and legacy databases WWW
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CAP 4770 8 What Can Data Mining Do? Cluster Classify Categorical, Regression Semi-supervised Summarize Summary statistics, Summary rules Link Analysis / Model Dependencies Association rules Sequence analysis Time-series analysis, Sequential associations Detect Deviations
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CAP 4770 9 Data Mining Tasks Prediction Methods Use some variables to predict unknown or future values of other variables.
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