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Re: Model object as output after fitting the linear model
From: |
Markus |
Subject: |
Re: Model object as output after fitting the linear model |
Date: |
Mon, 22 Sep 2014 21:16:44 +0200 |
User-agent: |
Roundcube Webmail/1.0.0 |
Am 2014-09-22 13:53, schrieb Krishnaprasad:
Hallo all,
I am using Octave 3.8.0 to build a linear model that has several input
features and one output feature. I am using this model in order to
predict
the output for the given set of input features. When I searched on the
web
for statistical packages, I found the following functions: polyfit and
regress. But none of these functions returns me a model object which I
can
use it for prediction.
Can I kindly know from the forum is there a function in octave that
returns
me a model object for linear regression?
Something like that?
function f = fitml(y)
B = polyfit (1:length(y),y,1);
f = @(x) (B(1))*x + B(2);
end
octave:1> y = [0 1 3 2 4 3 6 5 6 7];
octave:2> model1 = fitml(y)
model1 =
@(x) B (1) * x + B (2)
octave:3> model1(192)
ans = 138.206060606061
octave:4> polyfit (1:length(y),y,1)
ans =
0.721212121212121 -0.266666666666668
octave:5> ans(1)*192+ans(2)
ans = 138.206060606061
And if you need informations about m and b
function f = fitml(y)
B = polyfit (1:length(y),y,1);
f.mdl = @(x) B(1)*x + B(2);
f.m = rats(B(1)); % this is a char!
f.b = rats(B(2)); % this is a char!
end
use f = fitml(y); and f.mdl(192) or f.m e.g.
But maybe I don't understand what you're looking for.
Best regards,
Krishnaprasad
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