Support Vector Machines: Maximum-Margin Classification
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Adapted from an appendix of my MS thesis. Support Vector Machine The support vector machine (SVM) solves the binary classification task. It is a supervised learning task where we have a set of examples x n ∈ R D along with their corresponding binary labels y n ∈ { 1 , − 1 } . Given a training set {( x 1 , y 1 ) , … , ( x N , y N )} we would like to estimate parameters of the model that will give the smallest classification error. In the case of binary classification, we divide the…
1Key Takeaways
- Adapted from an appendix of my MS thesis.
- Support Vector Machine The support vector machine (SVM) solves the binary classification task.
- It is a supervised learning task where we have a set of examples x n ∈ R D along with their corresponding binary labels y n ∈ { 1 , − 1 } .
- Given a training set {( x 1 , y 1 ) , … , ( x N , y N )} we would like to estimate parameters of the model that will give the smallest classification error.
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — ML reports that adapted from an appendix of my MS thesis.
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