We propose signature linear discriminant analysis (signature-LDA) as an extension of LDA that can be applied to signatures, which are known to be more ...
Linear Discriminant Analysis for Signatures. Seungil Huh and Donghun Lee. Abstract—We propose signature linear discriminant analysis. (signature-LDA) as an ...
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In pattern recognition, feature extraction techniques are widely employed to reduce the dimensionality of data and to enhance the discriminatory information.
We propose signature linear discriminant analysis (signature-LDA) as an extension of LDA that can be applied to signatures, which are known to be more ...
Aug 23, 2023 · Linear Discriminant Analysis (LDA) is a dimensionality reduction and classification technique commonly used in machine learning and pattern recognition.
Nov 27, 2023 · Linear discriminant analysis (LDA) is an approach used in supervised machine learning to solve multi-class classification problems.
Dec 14, 2023 · We introduce factorized linear discriminant analysis (FLDA), a novel method for linear dimensionality reduction.
Mar 20, 2024 · LDA works by projecting the data onto a lower-dimensional space that maximizes the separation between the classes.
Linear Discriminant Analysis (LDA) is a method used in classification and dimensionality reduction, particularly for datasets with numerous features.
Missing: Signatures. | Show results with:Signatures.
Oct 14, 2024 · Linear Discriminant Analysis (LDA) is a statistical technique for categorizing data into groups. It identifies patterns in features to distinguish between ...