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Understanding Linear Discriminators and SVMs by Khalifa Bakkar is a document available to read on EtoBox.

What is Understanding Linear Discriminators and SVMs about?

1. Linear discriminators use a linear combination of feature weights to classify examples as either +1 or -1. 2. The data can be augmented by adding an extra feature with a value of -1, allowing the threshold to be represented as another feature weight. 3. Mapping data points into a higher dimensional space can enable linear separation when the data is not originally linearly separable in the original feature space.

Author

Khalifa Bakkar

Language

EN