Data mining : practical machine learning tools and techniques / Ian H. Witten, Eibe Frank
Series: The Morgan Kaufmann series in data management systemsPublisher: Amsterdam : Morgan Kaufmann : Elsevier, cop. 2005Edition: 2nd. edDescription: xxxi, 525 P. : ill., diagr., tab.)ISBN: 008047702X; 9780080477022Subject(s): Artificial intelligenceDDC classification: 006.3,WIT Online resources: Click here to access online| Item type | Current location | Home library | Shelving location | Call number | URL | Status | Notes | Date due | Barcode | Item holds |
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Book
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Military College of Signals (MCS) | Military College of Signals (MCS) | General Stacks | 006.3,WIT (Browse shelf) | Link to resource | Available | Almirah No.7, Shelf No.3 | MCS32541 |
What’s It All About? (Page-3), Input: Concepts, Instances, Attributes (Page-41), Output: Knowledge Representation (Page-61), Algorithms: The Basic Methods (Page-83), Credibility: Evaluating What’s Been Learned(Page-143), Implementations: Real Machine Learning Schemes (Page-187), Transformations: Engineering The Input And Output(Page-285), Moving On: Extensions And Applications.Part II: The Weka Machine Learning Workbench(Page- 363), Introduction To Weka (Page-365) The Explorer(Page-369), The Knowledge Flow Interface (Page-427), The Experimenter (Page-437), The Command-Line Interface (Page-449), Embedded Machine Learning (Page-461), Writing New Learning Schemes (Page-471).
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