Metalearning: Applications to Data Mining
2008年11月 · Springer Science & Business Media
電子書
176
頁數
report評分和評論未經驗證 瞭解詳情
關於這本電子書
Metalearning is the study of principled methods that exploit metaknowledge to obtain efficient models and solutions by adapting machine learning and data mining processes. While the variety of machine learning and data mining techniques now available can, in principle, provide good model solutions, a methodology is still needed to guide the search for the most appropriate model in an efficient way. Metalearning provides one such methodology that allows systems to become more effective through experience.
This book discusses several approaches to obtaining knowledge concerning the performance of machine learning and data mining algorithms. It shows how this knowledge can be reused to select, combine, compose and adapt both algorithms and models to yield faster, more effective solutions to data mining problems. It can thus help developers improve their algorithms and also develop learning systems that can improve themselves.
The book will be of interest to researchers and graduate students in the areas of machine learning, data mining and artificial intelligence.
為這本電子書評分
請分享你的寶貴意見。
閱讀資訊
智能手機和平板電腦
手提電腦和電腦
你可以使用電腦的網絡瀏覽器聆聽在 Google Play 上購買的有聲書。
電子書閱讀器及其他裝置
如要在 Kobo 等電子墨水裝置上閱覽書籍，你需要下載檔案並傳輸到你的裝置。請按照說明中心的詳細指示，將檔案傳輸到支援的電子書閱讀器。
