Principles of Data Mining

Data Mining, the automatic extraction of implicit and potentially useful information from data, is increasingly used in commercial, scientific and other application areas. This book explains and explores the principal techniques of Data Mining: for classification, generation of association rules and...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Bramer, Max (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: London : Springer London, 2007.
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • Data for Data Mining
  • to Classification: Na¨ive 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
  • Association Rule Mining I
  • Association Rule Mining II
  • Clustering
  • Text Mining.