Open AccessMaking sense of high dimensional concrete data – a statistical approach
Author(s) -
A. Manoj,
K. S. Babu Narayan
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/615/1/012019
Subject(s) - dimensionality reduction , curse of dimensionality , variance (accounting) , interpretation (philosophy) , computer science , field (mathematics) , data mining , reduction (mathematics) , machine learning , statistics , mathematics , geometry , accounting , pure mathematics , business , programming language
Performance of concrete is dependent on a number of factors. It is difficult to understand the influence and interrelationship among these variables, when there are many. Dimensionality reduction techniques can yield the best possible data interpretation based on the variance in data, without loss of much of original information. This paper presents the application of dimensionality reduction technique for analysis of data and decision making in the field of Concrete Technology.