Linear discriminant analysis (LDA), normal discriminant analysis (NDA), canonical variates analysis (CVA), or discriminant function analysis is a generalization of Fisher's linear discriminant, a method used in statistics and other fields, to find a linear combination of

2025年2月10日 · Linear Discriminant Analysis (LDA) also known as Normal Discriminant Analysis is supervised classification problem that helps separate two or more classes by converting higher-dimensional data space into a lower-dimensional space.

线性判别分析（Linear Discriminant Analysis，LDA）的一种经典的线性学习方法（属于监督学习），这里先借用周志华教授的《机器学习》中的图片来做一个直观的展示：正如该图中展示的那样，LDA需要寻找一条合适的直线y=wTxy=w^Txy=wTx，使得数据集中的样例投影到该 ...

2019年11月10日 · In this article, we discovered the topic modeling for images and how we can use the image caption dataset to build the topic detection model. Specifically, we built the topic model using Gensim...

2024年9月1日 · Develop a novel LDA model with 0 and 2,0 -norm to improve accuracy and robustness. Design a simple and optimization algorithm based on the ADMM and threshold operators. Demonstrate the advantages of the proposed method by extensive experiments.

This article describes, through a simple example, usage of a Linear Discriminant Analysis (LDA) technique to classify particles in an image. We start with a very simple, almost pre-segmented, image containing different kind of cereals : corn, rice, pasta shells, pasta torris and lentils :

2024年11月10日 · 本文将重点探讨如何利用OpenCV实现线性判别分析（LDA）算法，并应用于图像特征提取，从而提升图像识别的准确性和效率。 线性判别分析（LDA）是一种经典的监督学习方法，主要用于降维和特征提取。 其核心思想是通过寻找一个投影矩阵，使得投影后的数据类内方差最小、类间方差最大，从而实现数据的最佳分类。 LDA的基本步骤如下： 计算类内散布矩阵（Sw）：反映同类样本之间的离散程度。 计算类间散布矩阵（Sb）：反映不同类样本之间的 …

2013年4月5日 · Two new extensions of latent Dirichlet allocation (LDA), denoted topic-supervised LDA (ts-LDA) and class-specific-simplex LDA (css-LDA), are proposed for image classification.

This repository contains the implementation of an image-based LDA model for use in semi-automation of the image annotation and data curation process. It uses unsupervised Latent Dirichlet Allocation (LDA), Scale-Invariant Feature Transform (SIFT), and ImageNet pre-trained Convolutional Neural Networks (CNNs) to group unlabeled images into ...

2013年11月1日 · Two new extensions of latent Dirichlet allocation (LDA), denoted topic-supervised LDA (ts-LDA) and class-specific-simplex LDA (css-LDA), are proposed for image classification.