Support Vector Machines
In support vector machines, each data item is plotted as a point in n-dimensional space (where n is the number of features). The value of each feature is the value of a particular coordinate.
Applications
- classify between disease group and non-disease group like a Decision Tree.
- prediction of membrane protein types in whole sequences.
- prediction of translation initiation sites in biological sub-sequences ref.
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