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Basics of Multivariate Analysis in Neuroimaging Data
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Detecting Trivariate Associations in High-Dimensional Datasets.

Chuanlu Liu1, Shuliang Wang1,2, Hanning Yuan1

  • 1School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China.

Sensors (Basel, Switzerland)
|April 12, 2022
PubMed
Summary

We introduce the Quadratic Optimized Trivariate Information Coefficient (QOTIC) to detect complex relationships among three variables in large datasets. QOTIC offers a more accurate, equitable, and efficient method for multivariable correlation detection than existing approaches.

Keywords:
correlationlarge datamaximal information coefficient (MIC)quadratic optimized trivariate information coefficient (QOTIC)trivariate associations

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Area of Science:

  • Data Mining
  • Statistical Analysis
  • Machine Learning

Background:

  • Detecting correlations in high-dimensional data is crucial for knowledge discovery.
  • Existing methods like the maximal information coefficient (MIC) are limited to bivariate correlations.
  • Multivariable and trivariate associations remain a significant challenge in data analysis.

Purpose of the Study:

  • To introduce a novel method, the Quadratic Optimized Trivariate Information Coefficient (QOTIC), for detecting trivariate associations.
  • To address the limitations of existing methods in capturing multivariable correlations.
  • To provide a more general, equitable, accurate, and efficient approach for correlation detection.

Main Methods:

  • Development of a novel quadratic optimization procedure to accurately estimate correlations.
  • Implementation of QOTIC with general test functions for broad applicability.
  • Evaluation of QOTIC's performance across various dataset sizes and noise levels.

Main Results:

  • QOTIC demonstrates high accuracy in measuring dependence among three variables.
  • The method shows superior generality and equitability compared to existing techniques.
  • QOTIC achieves higher accuracy and improved time-efficiency over previous methods.

Conclusions:

  • QOTIC is a powerful new tool for detecting multivariable correlations, particularly trivariate associations.
  • The method's performance is validated through extensive experimental results.
  • QOTIC advances the field of data mining by enabling more robust knowledge discovery.