Machine learning 

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

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