From e1e0f73028f1c3cd26bf6df3e848a9b58a2ab556 Mon Sep 17 00:00:00 2001 From: Karl Ezra Pilario Date: Mon, 29 May 2023 15:56:42 +0800 Subject: [PATCH] Add files via upload --- Linear_and_Logistic_Regression/LWR_gif.m | 33 +++++++++++++++++++++ Linear_and_Logistic_Regression/LWR_tau.gif | Bin 0 -> 2287531 bytes 2 files changed, 33 insertions(+) create mode 100644 Linear_and_Logistic_Regression/LWR_gif.m create mode 100644 Linear_and_Logistic_Regression/LWR_tau.gif diff --git a/Linear_and_Logistic_Regression/LWR_gif.m b/Linear_and_Logistic_Regression/LWR_gif.m new file mode 100644 index 0000000..c4e8850 --- /dev/null +++ b/Linear_and_Logistic_Regression/LWR_gif.m @@ -0,0 +1,33 @@ +clc; close all; rng(0); + +% Generate Sine Data Set +N = 100; % No. of training points +x = linspace(0,12,N)'; % Training data, x +y = sin(x) + 0.5*rand(N,1); % Training data, y +y = (y - mean(y))./std(y); % Standard scaling on y + +scatter(x,y,'b','filled','MarkerFaceAlpha',0.3); +grid on; box on; set(gcf,'Color','w'); + +xp = linspace(-2,14,200)'; % Finely spaces x values +yp = zeros(size(xp)); + +for tau = 0.1:0.02:3 + weighting = @(x,X,tau) exp(-(x-X).^2/(2*tau^2)); + for j = 1:length(xp) + W = diag(weighting(xp(j),x,tau)); + X = [ones(N,1), x]; + w = (X'*W*X)\(X'*W*y); % Locally weighted linear reg. + yp(j) = [1 xp(j)]*w; % Predict on xp(j) + end + + hold on; p = plot(xp,yp,'k','LineWidth',1.5); + set(gcf,"Position",[488,506.6,560,255.4]); + title(sprintf('LWR, tau = %.4f',tau)) + axis([-2 14 -3 3]); + + % For creating a GIF + % exportgraphics(gcf,'LWR_tau.gif','Append',true); + + pause(0.5); delete(p); +end diff --git a/Linear_and_Logistic_Regression/LWR_tau.gif b/Linear_and_Logistic_Regression/LWR_tau.gif new file mode 100644 index 0000000000000000000000000000000000000000..88e067db3a515b6172163e123385b04e149caa4d GIT binary patch literal 2287531 zcmeEt)l(eI6YUzX_%0IMU4whb;!be)5ZoOSU|DQ&cXxM(0E+~736h|}36>BcLhkpw 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