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- function plotFit(min_x, max_x, mu, sigma, theta, p)
- %PLOTFIT Plots a learned polynomial regression fit over an existing figure.
- %Also works with linear regression.
- % PLOTFIT(min_x, max_x, mu, sigma, theta, p) plots the learned polynomial
- % fit with power p and feature normalization (mu, sigma).
- % Hold on to the current figure
- hold on;
- % We plot a range slightly bigger than the min and max values to get
- % an idea of how the fit will vary outside the range of the data points
- x = (min_x - 15: 0.05 : max_x + 25)';
- % Map the X values
- X_poly = polyFeatures(x, p);
- X_poly = bsxfun(@minus, X_poly, mu);
- X_poly = bsxfun(@rdivide, X_poly, sigma);
- % Add ones
- X_poly = [ones(size(x, 1), 1) X_poly];
- % Plot
- plot(x, X_poly * theta, '--', 'LineWidth', 2)
- % Hold off to the current figure
- hold off
- end
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