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Data Mining

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  1. Data Mining

  2. Models Created by Data Mining • Linear Equations • Rules • Clusters • Graphs • Tree Structures • Recurrent Patterns

  3. Knowledge Discovery in Databases (KDD) • Select target data • Preprocess data • Transform (if necessary) • Data mine information • Interpret discovered structures

  4. Dependant and Independent Variables • Dependant Variable - Attribute to be predicted. • Independent Variable - Attributes used for making the prediction.

  5. Fields Contributing to Data Mining • Database Technology • Statistics • Machine Learning • High Performance Computing • Pattern Recognition • Neural Networks • Data Visualization • Information Retrieval

  6. Applications of Data Mining • Decision Making • Process Control • Information Management • Query Processing

  7. Methods of Data Reduction • Drill-down analysis • Clustering • Aggregation • Simple Tabulation

  8. Exploratory Data Analysis (EDA) • Distributions of Variables • Correlation Matrices • Multi-way Frequency Tables • Cluster Analysis • Classification Trees • Other multivariate techniques

  9. Statistical Methods Used in Data Mining • Regression Analysis • Standard Distribution • Cluster Analysis

  10. Industries Using Data Mining • Banking • Insurance • Medicine • Retail • Security • Sciences

  11. Financial Uses of Data Mining • Fraud Detection • Money Laundering Detection • Risk Management

  12. Medical Uses of Data Mining • Chemical Compounds • Genetic Material • Predictive Treatment Models

  13. Retail Uses of Data Mining • Direct Marketing • Store Design • Store Operations

  14. Security Uses of Data Mining • Assess crime patterns • Homeland Security • Identification of suspicious activities • Pre-screening

  15. Scientific Uses of Data Mining • Image analysis • Classification of large data sets

  16. Other Novel Uses for Data Mining • NBA’s Advanced Scout Program • Firefly

  17. Predictive Analytics • An advanced form of data mining that makes prediction models for the behavior of variables in large data sets. • Highly specialized for each application

  18. Uses of Predictive Analytics • Cost-Benefit Analysis • Predicting Customer Behavior • Reducing Costs

  19. Financial Uses of Predictive Analytics • Credit Ratings • Economic Prediction Models • Federal Reserve

  20. Text Mining • Extracts data from unstructured data sets • Allows for data mining of large data sets that are not databases

  21. Sentiment Analysis • Uses semantic techniques and keywords to detect favorable and unfavorable opinions toward specific subjects.

  22. Privacy Concerns with Data Mining • Big Brother • Puts too much power into the hands of Governmental Security Forces

  23. False Positives in Data Mining for Security Reasons • Costs the people and the Government • Subject of controversy and civilian mistrust

  24. Data Mining as Another Tool for Security • Government doesn’t wish to interfere in civilian life • Actual intrusions of privacy incur legal costs • Useful for correlating with other sources of data

  25. Visual and Speech Processing • Examining large amounts of real-time input for specific data and relationships between data • Requires a certain amount of predictive modeling

  26. Data Mining is an Essential Use of Computers • It makes the previously impossible possible • Powerful tool for progress and understanding • Lasting Impact

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