Created
January 4, 2015 09:05
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curve fitting
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%%% reference : | |
%%% (1) パターン認識と機械学習 | |
%%% (2) http://aidiary.hatenablog.com/entries/2014/01/22 | |
clear all; | |
N = 100; | |
EPS = 0.01; | |
ETA = 0.1; | |
LOOP = 500; | |
D = 2; % in | |
M = 4; % hidden | |
K = 1; % out | |
X = linspace(-5, 5, N); | |
bias = ones(size(X)); | |
% T = sin(X); | |
T = sin(X) + 0.25 * randn(size(X)); | |
w1 = randn(M, D); | |
w2 = randn(K, M); | |
function error = sum_sq_error(x, t, w1, w2) | |
error = 0.0; | |
z = tanh(w1 * x); | |
y = w2 * z; | |
error += sum((y - t).^2) / 2; | |
end | |
xs = vertcat(ones(size(X)), X); | |
errs = zeros(1, LOOP); | |
c = 0; | |
%err1 = 0; | |
%err2 = Inf; | |
for _ = 1:LOOP | |
%while abs(err2 - err1) > EPS | |
for n = 1:N | |
x = [1; X(n)]; | |
% x = vertcat(ones(size(X)), X); | |
z = tanh(w1 * x); | |
y = w2 * z; | |
d2 = y - T(n); | |
d1 = (1 - z.^2) .* w2' * d2; | |
% d1(j) = (1 - z(j)^2) * w2(j) * d2; | |
w1 -= ETA * d1 * x'; | |
w2 -= ETA * d2 * z'; | |
end | |
errs(_) = sum_sq_error(xs, T, w1, w2); | |
%err1 = err2; | |
%err2 = sum_sq_error(xs, T, w1, w2); | |
%c += 1; | |
end | |
Z = tanh(w1 * vertcat(ones(size(X)), X)); | |
Y = w2 * Z; | |
figure(1) | |
plot(X, T, 'o', X, Y) | |
% plot(errs(50:LOOP)) |
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%%% reference : | |
%%% (1) パターン認識と機械学習 | |
%%% (2) http://yuki-koyama.hatenablog.com/entry/2014/05/04/132552 | |
%%% (3) http://taku-k.hatenablog.com/entry/2013/11/16/203644 | |
% clear all; | |
N = 100; % number of sampling | |
RES = 200; % resolution of output curves | |
L = 1; % | |
%rbf = 'gauss'; | |
x = linspace(-5, 5, N); | |
y = sin(x) + 0.25 * randn(size(x)); | |
X = linspace(-5, 5, RES); | |
%if strcmp(rbf, 'gauss') | |
h = zeros(N, N); | |
for i = 1 : N | |
for j = 1 : N | |
r = abs(x(i) - x(j)); | |
h(i, j) = normpdf(r); | |
end | |
end | |
w = pinv(h) * y'; | |
w2 = (L * eye(N) + h' * h) \ (y * h)'; | |
dist = abs(ones(RES, 1) * x - X' * ones(1, N)); | |
%%% equivalent to: | |
%for i = 1 : NUM_PLOT | |
% dist = abs(X(i) * ones(1, N) - x); | |
% % Y(i) = dot(ws, normpdf(x, X(i), 1)); | |
% Y(i) = dot(w, normpdf(dist)); | |
%end | |
ND = normpdf(dist); | |
Y = ND * w; | |
Y2 = ND * w2; | |
%end | |
figure(1) | |
subplot(2, 1, 1); | |
plot(x, y, 'o', 'MarkerSize', 5, X, Y, X, Y2); | |
axis([-5, 5, -1.5, 1.5]); | |
title('Gaussian') | |
legend('sin(x) + \epsilon', 'least-squares solution', 'after regularization', 'Location', 'NorthEastOutside'); | |
%if strcmp(rbf, 'poly') | |
M = 12; % degree of polynomial | |
h = zeros(N, M); | |
for j = 1 : M | |
h(:, j) = x .^ (j-1); | |
end | |
w = pinv(h) * y'; | |
w2 = (L * eye(M) + h' * h) \ (y * h)'; | |
X2 = zeros(size(X)); | |
for i = 1 : M | |
X2(i, :) = X.^(i-1); | |
end | |
Y = w' * X2; | |
Y2 = w2' * X2; | |
%end | |
subplot(2, 1, 2); | |
plot(x, y, 'o', 'MarkerSize', 5, X, Y, X, Y2); | |
axis([-5, 5, -1.5, 1.5]); | |
title('Polynomial') | |
legend('sin(x) + \epsilon', 'least-squares solution', 'after regularization', 'Location', 'NorthEastOutside'); | |
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