On-line Linear Discriminant Classifier

Name: On-line Linear Discriminant Classifier
Brand: VDM Verlag Dr. Müller
SKU: 9783639175868
Price: 253.97 RON
Availability: InStock

and its Application to Delayed Labelling

Autor: Catrin Plumpton

Limbă:

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Editura: VDM Verlag Dr. Müller

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253.97 lei

We present an on-line Linear Discriminant Classifier for streaming data (O-LDC). This is an adaptati...

Informații despre carte

Autor

Catrin Plumpton

Limbă

engleză

Legare

Carte - Carte broșată

Publicat

2009

Pagini

EAN

9783639175868

Enbook ID

06825874

Editura

VDM Verlag Dr. Müller

Greutate

112

Dimensiuni

150 x 220 x 4

Descriere completă

We present an on-line Linear Discriminant Classifier for streaming data (O-LDC). This is an adaptation of the Linear Discriminant Classifier, with the class means and the inverse covariance matrix re-calculated after each new data point. The classifier satisfies the properties of an on-line classifier; it learns from a single pass through the data, uses limited memory and processing power, and exhibits any-time learning. We compare the O-LDC with on-line versions of the Perceptron and balanced Winnow classifiers. Comparisons are carried out across a series of static data sets made up of two classes. The O-LDC shows higher accuracy and a better learning rate than its counterparts. As a second task we consider delayed labelling. We propose two strategies. The passive strategy 'waits' for the correct label of a data point before using it to update the classifier. The aggressive strategy, makes use of naďve labelling, using the predicted label of a data point to update the classifier. The strategies are compared across a series of static data sets. The final accuracy of both strategies was comparable, though the passive strategy showed a better learning pattern.

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On-line Linear Discriminant Classifier

and its Application to Delayed Labelling

Informații despre carte

Descriere completă

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