基于matlab的PCA特征提取,归一化PCA特征提取,LDA特征提取以及归一化LDA特征提取四种算法的数据分类对比+操作视频

clc; clear; close all; warning off; addpath(genpath(pwd)); data = dlmread("wine.csv",","); X = data(:,2:end); y = data(:,1); [Dpca, Wpca] = pca(X); Xm = bsxfun(@minus, X, mean(X)); Xproj = project(Xm, Wpca(:,1:2)); cumsum(Dpca) / sum(Dpca) % the first component accounts for 99% of total Variance wine1 = Xproj(find(y == 1), :); wine2 = Xproj(find(y == 2), :); wine3 = Xproj(find(y == 3), :); figure; hold on; plot(wine1(:,1), wine1(:,2), "ro", "markersize", 10, "linewidth", 3); plot(wine2(:,1), wine2(:,2), "go", "markersize", 10, "linewidth", 3); plot(wine3(:,1), wine3(:,2), "bo", "markersize", 10, "linewidth", 3); title("PCA (original data)") %% Linear Discriminant Analysis without Normalization [Dlda,Wlda] = lda(X,y); Xproj = project(Xm, Wlda(:,1:2)); wine1 = Xproj(find(y == 1), :); wine2 = Xproj(find(y == 2), :); wine3 = Xproj(find(y == 3), :); figure; hold on; plot(wine1(:,1), wine1(:,2), "ro", "markersize", 10, "linewidth", 3); plot(wine2(:,1), wine2(:,2), "go", "markersize", 10, "linewidth", 3); plot(wine3(:,1), wine3(:,2), "bo", "markersize", 10, "linewidth", 3); title("LDA (original data)") %% Fix PCA by using Normalization Xnew = zscore(X); [Dpca, Wpca] = pca(Xnew); Xm = bsxfun(@minus, Xnew, mean(Xnew)); Xproj = project(Xm, Wpca(:,1:2)); cumsum(Dpca) / sum(Dpca) wine1 = Xproj(find(y == 1), :); wine2 = Xproj(find(y == 2), :); wine3 = Xproj(find(y == 3), :); figure; hold on; plot(wine1(:,1), wine1(:,2), "ro", "markersize", 10, "linewidth", 3); plot(wine2(:,1), wine2(:,2), "go", "markersize", 10, "linewidth", 3); plot(wine3(:,1), wine3(:,2), "bo", "markersize", 10, "linewidth", 3); title("PCA (Normalized)") %% compare against LDA with Normalization [Dlda,Wlda] = lda(Xnew,y); Xproj = project(Xm, Wlda(:,1:2)); wine1 = Xproj(find(y == 1), :); wine2 = Xproj(find(y == 2), :); wine3 = Xproj(find(y == 3), :); figure; hold on; plot(wine1(:,1), wine1(:,2), "ro", "markersize", 10, "linewidth", 3); plot(wine2(:,1), wine2(:,2), "go", "markersize", 10, "linewidth", 3); plot(wine3(:,1), wine3(:,2), "bo", "markersize", 10, "linewidth", 3); title("LDA (Normalized)")