Linear discriminant analysis: A detailed tutorial

By Alaa Tharwat, Tarek Gaber, Abdelhameed Ibrahim, Aboul Ella Otifey Hassanien. AI Communications, 2017

890 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Artificial Intelligence, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/22b61f2b9a87f990446cbda77d89351c792c92fd

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Analytical Chemistry

1. Christine Dewi
2. Rung Ching Chen
3. Rezzy Eko Caraka
4. Su-Wen Huang

In Artificial Intelligence

1. Christine Dewi
2. Rung Ching Chen
3. Rezzy Eko Caraka
4. Su-Wen Huang

In Computer Vision and Pattern Recognition

1. Rung Ching Chen

Citations in the corpus

• Overview and comparative study of dimensionality reduction techniques for high dimensional data (2020, neutral): “Linear Discriminant Analysis (LDA) is a supervised LDRT which applies the linear combination of features as a linear classifier for DR [130– 134] .”
• Selecting critical features for data classification based on machine learning methods (2020, methodology): “The type of distance metric used in this method is Euclidean distance described in the equation below: Linear Discriminant Analysis (LDA) [85] usually used as a dimensionality decrease technique in the pre-processing step for classification and machine learning applications.”