What is the difference between Parametric and Non-Parametric Models?

AI Interview Question #16

What is the difference between Parametric and Non-Parametric Models?

Answer:
Parametric and Non-Parametric models differ in how they learn from data and make predictions.

✅ Parametric Models:

Have a fixed number of parameters (e.g., weights in Linear Regression).

Assume a specific mathematical form for data distribution.

Examples: Linear Regression, Logistic Regression, Naïve Bayes.
✅ Non-Parametric Models:

Do not assume a fixed number of parameters.

Can adapt to complex and irregular patterns in data.

Examples: Decision Trees, K-Nearest Neighbors (KNN), Support Vector Machines (SVM).
Key Difference:

Parametric models are faster but may underfit if assumptions are wrong.

Non-Parametric models are flexible but can overfit if not regularized properly.
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Видео What is the difference between Parametric and Non-Parametric Models? канала Sharmistha Majumder