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[regression] some more files

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This commit is contained in:
Jan Benda 2020-12-21 21:33:13 +01:00
parent f5c3bb6139
commit f6b52d32cb
7 changed files with 14 additions and 14 deletions
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4
pointprocesses/lecture/pointprocessscetchA.eps
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@ -1,7 +1,7 @@
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%%Title: pointprocessscetchA.tex %%Title: pointprocessscetchA.tex
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%%CreationDate: Thu Dec 17 09:43:52 2020 %%CreationDate: Mon Dec 21 20:05:25 2020
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@ -441,7 +441,7 @@ SDict begin [
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/CreationDate (Thu Dec 17 09:43:52 2020) /CreationDate (Mon Dec 21 20:05:25 2020)
/DOCINFO pdfmark /DOCINFO pdfmark
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} ifelse } ifelse

16
pointprocesses/lecture/pointprocessscetchA.pdf
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@ -43,12 +43,12 @@ endobj
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@ -58,8 +58,8 @@ endstream
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/CreationDate(Thu Dec 17 09:43:52 2020) /CreationDate(Mon Dec 21 20:05:25 2020)
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/Title(pointprocessscetchA.tex) /Title(pointprocessscetchA.tex)
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/Subject(gnuplot plot)>>endobj /Subject(gnuplot plot)>>endobj
@ -77,7 +77,7 @@ xref
0000000814 00000 n 0000000814 00000 n
trailer trailer
<< /Size 10 /Root 1 0 R /Info 2 0 R << /Size 10 /Root 1 0 R /Info 2 0 R
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>> >>
startxref startxref
2571 2571

4
pointprocesses/lecture/pointprocessscetchB.eps
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@ -1,7 +1,7 @@
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%%Title: pointprocessscetchB.tex %%Title: pointprocessscetchB.tex
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%%CreationDate: Thu Dec 17 09:43:53 2020 %%CreationDate: Mon Dec 21 20:05:26 2020
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@ -441,7 +441,7 @@ SDict begin [
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/DOCINFO pdfmark /DOCINFO pdfmark
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pointprocesses/lecture/pointprocessscetchB.pdf
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2
regression/code/gradientDescent.m
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@ -34,7 +34,7 @@ function gradmse = meanSquaredGradient(x, y, func, p)
ph = eye(length(p))*h; % ... for each parameter ph = eye(length(p))*h; % ... for each parameter
mse = meanSquaredError(x, y, func, p); mse = meanSquaredError(x, y, func, p);
for i = 1:length(p) % for each coordinate ... for i = 1:length(p) % for each coordinate ...
msepi = meanSquaredError(x, y, func, p + ph(:,i)); msepi = meanSquaredError(x, y, func, p(:) + ph(:,i));
gradmse(i) = (msepi - mse)/h; gradmse(i) = (msepi - mse)/h;
end end
end end

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regression/exercises/exp2plot.pdf
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regression/exercises/gradientdescent.m
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@ -29,7 +29,7 @@ end
function gradmse = msegradient(t, x, func, p) function gradmse = msegradient(t, x, func, p)
gradmse = zeros(size(p)); gradmse = zeros(size(p));
h = 1e-3; % stepsize for derivative h = 1e-7; % stepsize for derivative
ph = eye(length(p))*h; % ... for each parameter ph = eye(length(p))*h; % ... for each parameter
mse = meansquarederror(t, x, func, p); mse = meansquarederror(t, x, func, p);
for i = 1:length(p) % for each coordinate ... for i = 1:length(p) % for each coordinate ...