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# curve_fitting | |||
# 1. Least-Squares | |||
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# Set 1 | |||
Given Function: | |||
y = 0.3745 + 0.98644x + 0.84564x^-1 | |||
Regression Function: | |||
y = 0.3745 + 0.9864x + 0.8456x^-1 | |||
R2: | |||
0.9996 | |||
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# Set 2 | |||
Given Function: | |||
y = -11.4887 + 7.143817x - 1.04121x^2 + 0.046676x^3 | |||
Regression Function: | |||
y = -11.4887 + 7.1438x - 1.0412x^2 + 0.0467x^3 | |||
R2: | |||
0.8290 | |||
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# Set 3 | |||
Given Function: | |||
y = 4.0046e^(-1.5x) + 2.9123e^(-0.3x) + 1.5647e^(-0.05) | |||
Regression Function: | |||
y = 4.0046e^(-1.5x) + 2.9123e^(-0.3x) + 1.5647e^(-0.05) | |||
R2: | |||
0.9971 | |||
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# 2. Cost Logistic | |||
cost = 10.1590 | |||
gradient = 101.0435 | |||
![alt text](plot1.png) |