Home
This Title All WIREs
WIREs RSS Feed
How to cite this WIREs title:
WIREs Comp Stat

Tensor sufficient dimension reduction

Full article on Wiley Online Library:   HTML PDF

Can't access this content? Tell your librarian.

Tensor is a multiway array. With the rapid development of science and technology in the past decades, large amount of tensor observations are routinely collected, processed, and stored in many scientific researches and commercial activities nowadays. The colorimetric sensor array (CSA) data is such an example. Driven by the need to address data analysis challenges that arise in CSA data, we propose a tensor dimension reduction model, a model assuming the nonlinear dependence between a response and a projection of all the tensor predictors. The tensor dimension reduction models are estimated in a sequential iterative fashion. The proposed method is applied to a CSA data collected for 150 pathogenic bacteria coming from 10 bacterial species and 14 bacteria from one control species. Empirical performance demonstrates that our proposed method can greatly improve the sensitivity and specificity of the CSA technique. WIREs Comput Stat 2015, 7:178–184. doi: 10.1002/wics.1350 This article is categorized under: Statistical Learning and Exploratory Methods of the Data Sciences > Image Data Mining Statistical and Graphical Methods of Data Analysis > Nonparametric Methods Statistical Learning and Exploratory Methods of the Data Sciences > Pattern Recognition
The flowchart of SIDRA algorithm.
[ Normal View | Magnified View ]
Plotted in the left panel is the projection of 150 pathogenic bacteria on the first two dimension reduction directions. In the right panel, we compare the prediction error of SIR‐450 min (blue line), SIDRA‐450 min (green line) using data collected 450 min after exposing colorimetric sensor array (CSA) to the bacteria and SIDRA_ALL (red line) using all the time points from 120 min to 600 min, where measurement was taken every 30 min.
[ Normal View | Magnified View ]
Digital images of 10 pathogenic bacteria at full vapor pressure at 300 K.
[ Normal View | Magnified View ]

Browse by Topic

Statistical Learning and Exploratory Methods of the Data Sciences > Pattern Recognition
Statistical Learning and Exploratory Methods of the Data Sciences > Image Data Mining
Statistical and Graphical Methods of Data Analysis > Nonparametric Methods

Access to this WIREs title is by subscription only.

Recommend to Your
Librarian Now!

The latest WIREs articles in your inbox

Sign Up for Article Alerts