Machine learning
Machine learning (support vector machine)
Description
Support vector machine
• Overview (What is a SVMs? Structure of a SVMs)
• How to build the model
Key concept of SVMs
Mathematical formula
• How to test the model
• Strengths and weakness
Strengths: Able to handle large feature space; be able to deal with the interaction between nonlinear features; no need to rely on the entire data
Weaknesses: The efficiency is not very high when the observation samples are many; sometimes it’s hard to find a proper kernel function.
• Summarize the research conducted using SVMs to predict hospital-associated infection (at least 6 examples)
Answer preview to machine learning
APA
2064 words
