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README.md
boussinesq_lookup.m
cost_logistic.m
initializeData.m
least_squares.m
plot1.png
problem_1_data.m
setdefaults.m

README.md

curve_fitting

1. Least-Squares

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

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

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

2. Cost Logistic

cost = 10.1590 gradient = 101.0435 alt text

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