User:Francis Tyers/Perceptron
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Revision as of 19:58, 8 November 2014 by Francis Tyers (talk | contribs)
A perceptron is a classifier that
The classifier consists of:
- Binary features
- Weights
Example
Here is a worked example of a perceptron applied to the task of lexical selection. Lexical selection is the task of choosing a target translation for a given source word in a context out of a set of possible translations . A perceptron makes a classification decision for a single class, so we need to train a separate perceptron for each possible target word selection.
In the example,
- = estació
- = {season, station}
- = season
Features
The features we will be working with are ngram contexts around the "problem word".
Training data
_ sec |
1 |
_ de el any |
1 |
_ de tren |
0 |
_ de el línia |
0 |
_ humit |
1 |
_ plujós |
1 |
un _ a |
0 |