In this article, a temperature drift compensation method based on a multivariate temperature field is proposed to fill this gap. Combining the theoretical basis of FOG and the structure of a ...

Isolation Forest detects anomalies by isolating observations. It builds binary trees (called iTrees) by recursively ...

We compared the performance of three widely used linear multivariate methods for autofluorescence spectroscopic tissues differentiation. Principal component analysis (PCA), partial least squares (PLS) ...

Therefore, this Methods Group will help define and support responsible AI use across four of the leading evidence synthesis organizations, including the Cochrane Collaboration, the Campbell ...

This article will cover the theory underpinning multivariate analysis of variance (MANOVA), which expands on the capabilities of ANOVA, the types of MANOVA and a worked example of the test.

Discover how multivariate methods in data science enhance predictive analytics for more accurate forecasting and deeper insights.

Discover how multivariate analysis is transforming target identification in cancer drug discovery by moving beyond traditional methods.

Discover how multivariate statistical methods can transform your data analysis for more accurate insights and predictions.

This module aims to introduce methodological, theoretical and applied foundations of some widely-used classical multivariate methods and modern high-dimensional methods. Further details are available ...