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Polynomial regression: Difference between revisions
→{{header|Mathematica}}
(J: note about precision) |
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Note that this implementation does not use floating point numbers, so we do not introduce floating point errors. Using exact arithmetic has a speed penalty, but for small problems like this it is inconsequential.
=={{header|Mathematica}}==
Using the built-in "Fit" function.
<lang Mathematica>data = Transpose@{Range[0, 10], {1, 6, 17, 34, 57, 86, 121, 162, 209,
262, 321}};
Fit[data, {1, x, x^2}, x]</lang>
Result:
<pre>1 + 2x + 3x^2</pre>
=={{header|MATLAB}}==
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2.999999999999998 2.000000000000019 0.999999999999956</lang>
=={{header|Octave}}==
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