SciPy - Curve Fitting and Regression
Which of the following best describes the output of
scipy.optimize.curve_fit after fitting a custom model?Which of the following best describes the output of scipy.optimize.curve_fit after fitting a custom model?
easy📝 Conceptual Q2 of 15
Step-by-Step Solution
Solution:
Step 1: Recall the return values of
The function returns two items: the best-fit parameters and the covariance matrix estimating parameter uncertainties.curve_fitStep 2: Eliminate incorrect options
It does not return residuals, success flags, or plots directly.Final Answer:
A tuple containing the optimized parameters and the covariance matrix -> Option DQuick Check:
Output = (parameters, covariance) [OK]
Quick Trick: Remember:
curve_fit returns params and covariance [OK]Common Mistakes:
- Expecting residuals directly from
curve_fit - Thinking it returns a success flag
- Assuming it generates plots automatically
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