They can take the feature space into higher dimensions to solve the problem.
D.
They use the sigmoid function to classify the data points.
The Answer Is:
C
This question includes an explanation.
Explanation:
SVM models can use kernel functions to map the input data into higher-dimensional feature spaces, where linear separation is possible. This allows SVM models to handle non-linear problems effectively. References: CertNexus Certified Artificial Intelligence Practitioner, Support vector machine - Wikipedia
AIP-210 PDF/Engine
Printable Format
Value of Money
100% Pass Assurance
Verified Answers
Researched by Industry Experts
Based on Real Exams Scenarios
100% Real Questions
Get 65% Discount on All Products,
Use Coupon: "ac4s65"