TY  - GEN
AU  - Witten,Ian H.
TI  - Data mining: practical machine learning tools and techniques 
SN  - 008047702X
U1  - 006.3,WIT 
PY  - 2005///
CY  - Amsterdam
PB  - Morgan Kaufmann, Elsevier
KW  - Artificial intelligence
N1  - 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)
UR  - http://link.libris.kb.se/sfxmah?url_ver=Z39.88-2004&ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&rfr_id=info:sid/sfxit.com:opac_856&url_ctx_fmt=info:ofi/fmt:kev:mtx:ctx&sfx.ignore_date_threshold=1&rft.object_id=1000000000364728&svc_val_fmt=info:ofi/fmt:kev:mtx:sch_svc&
ER  -