[Solved] Given data with outliers, how can polynomial fitting be adapted to reduce outlier impact? — Ans: Use weighted polynomial fitting giving less weight to outliers | SciPy

SciPy - Curve Fitting and Regression

Given data with outliers, how can polynomial fitting be adapted to reduce outlier impact?

ARemove polyfit and use mean calculation

BIncrease polynomial degree to fit outliers exactly

CUse weighted polynomial fitting giving less weight to outliers

DFit polynomial only to x values

Step-by-Step Solution

Solution:

Step 1: Understand outlier effect on fitting
Outliers can distort polynomial fit if treated equally.
Step 2: Use weighted fitting to reduce outlier influence
Assigning lower weights to outliers reduces their impact on the fit.
Final Answer:
Use weighted polynomial fitting giving less weight to outliers -> Option C
Quick Check:
Weighted fitting reduces outlier effect [OK]

Quick Trick: Weight data points to lessen outlier influence [OK]

Common Mistakes:

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Given data with outliers, how can polynomial fitting be adapted to reduce outlier impact?