heat map (pearson correlation)  (Minitab Inc)

Journal: Scientific Reports

Article Title: Integrating EPSOSA-BP neural network algorithm for enhanced accuracy and robustness in optimizing coronary artery disease prediction

doi: 10.1038/s41598-024-82184-2

Figure Lengend Snippet: Pearson heat map after UCI data augmentation.

Article Snippet: \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\rho = \frac{Cov(X,Y)}{{\sigma_{X} \sigma_{Y} }}$$\end{document} In order to show the one-hot encoded data in detail, so as to determine whether there is a need for subsequent dimensionality reduction, this paper conducted Pearson heat map correlation analysis on UCI data and Kaggle data.

Techniques:

Journal: Scientific Reports

Article Title: Integrating EPSOSA-BP neural network algorithm for enhanced accuracy and robustness in optimizing coronary artery disease prediction

doi: 10.1038/s41598-024-82184-2

Figure Lengend Snippet: Pearson heat map after Kaggle data augmentation.

Article Snippet: \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\rho = \frac{Cov(X,Y)}{{\sigma_{X} \sigma_{Y} }}$$\end{document} In order to show the one-hot encoded data in detail, so as to determine whether there is a need for subsequent dimensionality reduction, this paper conducted Pearson heat map correlation analysis on UCI data and Kaggle data.

Techniques:

Journal: Frontiers in Plant Science

Article Title: Triploidy in Citrus Genotypes Improves Leaf Gas Exchange and Antioxidant Recovery From Water Deficit

doi: 10.3389/fpls.2020.615335

Figure Lengend Snippet: Heat map of correlation matrix of physiological and biochemical variables found in (A) diploid and (B) triploid varieties under water deficit conditions. Correlation coefficient was calculated based on Pearson’s correlation at significant level (α < 0.05). Red and blue colors indicate positive and negative effects, respectively. Color intensity is proportional to the correlation coefficients, according to the figure legend. The white square corresponds to non-significant correlation ( P -value > 0.05).

Article Snippet: Heat map of Pearson’s correlation was performed with RStudio software.

Techniques: