{ "item_title" : "Principles of Data Mining", "item_author" : [" Max Bramer "], "item_description" : "Introduction to Data Mining.- Data for Data Mining.- Introduction to Classification: Na ve Bayes and Nearest Neighbour.- Using Decision Trees for Classification.- Decision Tree Induction: Using Entropy for Attribute Selection.- Decision Tree Induction: Using Frequency Tables for Attribute Selection.- Estimating the Predictive Accuracy of a Classifier.- Continuous Attributes.- Avoiding Overfitting of Decision Trees.- More About Entropy.- Inducing Modular Rules for Classification.- Measuring the Performance of a Classifier.- Dealing with Large Volumes of Data.- Ensemble Classification.- Comparing Classifiers.- Associate Rule Mining I.- Associate Rule Mining II.- Associate Rule Mining III.- Clustering.- Mining.- Classifying Streaming Data.- Classifying Streaming Data II: Time-dependent Data.- An Introduction to Neural Networks.- Appendix A - Essential Mathematics.- Appendix B - Datasets.- Appendix C - Sources of Further Information.- Appendix D - Glossary and Notation.- Appendix E - Solutions to Self-assessment Exercises.- Index.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/1/44/717/492/1447174925_b.jpg", "price_data" : { "retail_price" : "54.99", "online_price" : "54.99", "our_price" : "54.99", "club_price" : "54.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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