Difference between revisions of "User:Francis Tyers/Perceptron"
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The classifier consists of: |
The classifier consists of: |
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* An input vector, <math>x</math> |
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* Binary features |
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* A weight vector, <math>w</math> |
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* Threshold, <math>\theta</math> |
* Threshold, <math>\theta</math> |
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Revision as of 22:33, 8 November 2014
A perceptron is a classifier that
The classifier consists of:
- An input vector,
- A weight vector,
- Threshold,
Learning algorithm
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". These can be extracted from the word alignments calculated from a parallel corpus.
Catalan | English |
---|---|
Durant l' estació seca les pluges són escasses. | During the dry season it rains infrequently. |
L' estiu és una estació de l' any. | Summer of one of the seasons of the year. |
Barcelona-Sants és una estació de tren a Barcelona. | Barcelona-Sants is a train station in Barcelona. |
... |
Training data
- s = estació, t* = season
_ sec |
1 |
_ de el any |
1 |
_ de tren |
0 |
_ de el línia |
0 |
_ humit |
1 |
_ plujós |
1 |
un _ a |
0 |
Feature vector
This is the above training data expressed as an input vector to the perceptron.
_ sec | _ de el any | _ de tren | _ de la línia | _ humit | _ plujós | un _ a | ||
---|---|---|---|---|---|---|---|---|
1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | |
0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | |
0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | |
0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | |
0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | |
0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | |
0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
Weight vector
_ sec | _ de el any | _ de tren | _ de la línia | _ humit | _ plujós | un _ a |
0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |