This concise and approachable introduction to data mining selects a mixture of data mining techniques originating from statistics, machine learning and databases, and presents them in an algorithmic approach. Aimed primarily at undergraduate readers, it presents not only the fundamental principles and con...
The chapter includes an overview of data mining, followed by its evolution, methods, technologies, applications, and future.Multimedia ISData Warehousing & Mining Concepts Methodologies Tools & Applications
Data mining involves exploring and analyzing large blocks of information to glean meaningful patterns and trends. It is used in credit risk management,fraud detection, and spam filtering. It also is a market research tool that helps reveal the sentiment or opinions of a given group of people. T...
MiningWarehouse WebWith an enormous amount of data stored in databases and data warehouses, it is increasingly important to develop powerful tools for analysis of such data and mining interesting knowledge from it. Data mining is a process of inferring knowledge from such huge data. The main ...
Data Mining and Applications 作者:Li, Deren; Yang, Jie; Feng, Jufu; Wei, Shen 页数:218 ISBN:9780819442840 豆瓣评分 目前无人评价 + 加入购书单
Data mining tools and techniques help to predict business trends those can occur in near future. The goal of the paper... M Hazarika,M Rahman 被引量: 3发表: 2014年 TRENDS OF MINING TECHNIQUES, APPLICATIONS AND TOOLS: A SURVEY Mining, techniques, approaches and different areas of the ...
Taking analysis of the microarray data as an example, we spent the past decade developing many data mining strategies and software tools. It appears still... Y Pan,AB Tchagang,H Bérubé,... - International Conference on Industrial Engineering & Other Applications of Applied Intelligent Systems ...
Data mining is a process of uncovering patterns and finding anomalies and relationships in large datasets that can be used to make predictions about future trends.
High performance computers, such as multiclusters, clouds, and many-core systems, together with distributed and parallel data mining tools and algorithms, can provide effective solutions to analyze big data sets and obtain results in reasonable time. In general, this approach is based on the ...