An Investigation into the Use of a Neural Tree Classifier for Knowledge Discovery in OLAP Databases

【電子書籍なら、スマホ・パソコンの無料アプリで今すぐ読める！】

Modern OLAP platforms are capable of creating databases terabytes in size and present a significant challenge to the analyst with the goal of knowledge discovery. Artificial neural networks represent an aspect of machine learning that offers promise in this area. A neural map can learn to identify patterns in data of high dimensionality and a specific type of neural map, a neural tree classifier, can provide a hierarchical classification of the patterns identified. The investigation begins with a comparison of two neural tree classifiers and continues by illustrating how their application can allow the identification of multi-dimensional areas of analytical interest in an OLAP database. Finally, a novel OLAP exception "explain" technique is outlined, enabled through the use of a neural tree classifier in conjunction with discovery-driven exploration.画面が切り替わりますので、しばらくお待ち下さい。
※ご購入は、楽天kobo商品ページからお願いします。
※切り替わらない場合は、こちらをクリックして下さい。
※このページからは注文できません。

この商品の詳細を調べる

: 本・雑誌・コミック » 洋書 » COMPUTERS ＆ SCIENCE