The widespread scale effect always generates significant changes in the properties or
characteristics of management objects with different observation scales. Thus, this paper …

Traditional data mining application is an iterative feedback process which suffers from over-
depending on both business and data specialists' decision ability. This paper studies the …

With the high intensity and density of aerospace launch in China, aerospace project
materials management faces various challenges, such as multiple aerospace projects …

Large amounts of data are produced in system operation, and how to extract effective
information from these data has become an important research topic in the industrial …

Data dimension reduction is an important step for customer classification modeling, and
feature selection has been a research focus of the data dimension reduction field. This study …

In the era of big data, all types of data with increasing samples and high-dimensional
attributes are demonstrating their important roles in various fields, such as data mining …

In the present field of software applications, the prominently employed parameters for
parameters control are the kinds of models such as cloud computing, machine learning, and …

By combining linear discriminant analysis and Kmeans into a coherent framework, a
dimension reduction algorithm was recently proposed to select the most discriminative …

At present, the research work of dimension reduction at home and abroad is more about the
theoretical exploration and application research of specific dimension reduction methods …

High-dimensional data is ubiquitous in scientific research and industrial production fields. It
brings a lot of information to people, at the same time, because of its sparse and …