Perceptron

In machine learning, the perceptron is an algorithm for supervised classification of an input into one of several possible non-binary outputs. It is a type of linear classifier, i.e. a classification algorithm that makes its predictions based on a linear predictor function combining a set of weights with the feature vector. The algorithm allows for online learning, in that it processes elements in the training set one at a time.The perceptron algorithm was invented in 1957 at the Cornell Aeronautical Laboratory by Frank Rosenblatt.
Posts about Perceptron
  • Patterns Among Templates Lead to Clues About Entities

    … Extraction with Factzor 2.1.1 Mention Extraction via lists 2.1.2 Mention Extraction Via Templates 2.2 Training Set Extension 2.3 Non-Entities 2.4 Feature Generator 3 Machine Learning 3.1 Feature Screening 3.2 Perceptron Algorithm 3.3 Use of Class Hierarchy 3.4 Error Correcting Output Codes 3.5 Prediction Resolution 4. Results 4.1 Feature Benefit 5…

    Bill Slawski/ SEO by the Seain Google- 6 readers -
Get the top posts daily into your mailbox!