APPLICATION OF CANONICAL CORRELATION ANALYSIS ON SCIENCE PRODUCTION
نویسندگان
چکیده
منابع مشابه
On Generalized Canonical Correlation Analysis
In generalized canonical correlation analysis several sets of variables are analyzed simultaneously. This makes the method suited for the analysis of various types of data. For example, in marketing research, subjects may be asked to rate a set of objects on a set of attributes. For each individual, a data matrix can then be constructed where the objects are represented row-wise and the attribu...
متن کاملOn the Regularization of Canonical Correlation Analysis
By elucidating a parallel between canonical correlation analysis (CCA) and least squares regression (LSR), we show how regularization of CCA can be performed and interpreted in the same spirit as the regularization applied in ridge regression (RR). Furthermore, the results presented may have an impact on the practical use of regularized CCA (RCCA). More specifically, a relevant cross validation...
متن کاملApplication of canonical correlation analysis for identifying viral integration preferences
MOTIVATION Gene therapy aims at using viral vectors for attaching helpful genetic code to target genes. Therefore, it is of great importance to develop methods that can discover significant patterns around viral integration sites. Canonical correlation analysis is an unsupervised statistical tool that is used to describe the relations between two related views of the same semantic object, which...
متن کاملApplication of Canonical Correlation Analysis in Student Score Analysis Based on Data Analysis
Student score analysis is an important aspect in the educational research. The use of multivariate methods in the score analysis is essential to teachers or administrators who intend to explore more information from available score data. Canonical correlation analysis is the best technique to employ when the research problem has multiple variables. In this paper, we discuss the principle and ap...
متن کاملStochastic Canonical Correlation Analysis
We tightly analyze the sample complexity of CCA, provide a learning algorithm that achieves optimal statistical performance in time linear in the required number of samples (up to log factors), as well as a streaming algorithm with similar guarantees.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Engineering Technologies and Management Research
سال: 2020
ISSN: 2454-1907
DOI: 10.29121/ijetmr.v3.i8.2016.65