Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition provides a comprehensive introduction to machine learning concepts and their practical application to data mining. The book begins with the fundamentals of data mining, covering input preparation, output interpretation, algorithms, and evaluation of results. It then examines advanced machine learning techniques, including decision trees and rules, instance-based and linear models, data transformations, probabilistic methods, deep learning, learning beyond supervised and unsupervised approaches, and ensemble learning. The book emphasizes practical techniques for improving the performance of machine learning methods and applying them to real-world data mining problems. It is accompanied by the WEKA machine learning software toolkit, which provides an accessible environment for experimenting with a wide range of data mining and machine learning algorithms.

Ngôn ngữ:	eng
Tác giả:	Witten, Ian H., Frank, Eibe, Hall, Mark A., Pal, Christopher J.
Thông tin nhan đề:	Data Mining: Practical Machine Learning Tools and Techniques
Nhà xuất bản:	Morgan Kaufmann
Loại hình:	Giáo trình sách, tham khảo / Bộ sưu tập: Công nghệ thông tin
Mô tả vật lý:	621p.
Năm xuất bản:	2017