Cost-sensitive, Scalable and Adaptive Learning Using Ensemble Methods

Name: Cost-sensitive, Scalable and Adaptive Learning Using Ensemble Methods
Brand: VDM Verlag Dr. Müller
SKU: 9783639134421
Price: 350.24 RON
Availability: InStock

Theory and Application

Autor: Wei Fan

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Editura: VDM Verlag Dr. Müller

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350.24 lei

Prior work in inductive learning focused on generic§algorithms that sought to reduce complexity. Thu...

Informații despre carte

Autor

Wei Fan

Limbă

engleză

Legare

Carte - Carte broșată

Publicat

2009

Pagini

188

EAN

9783639134421

Enbook ID

06822143

Editura

VDM Verlag Dr. Müller

Greutate

296

Dimensiuni

150 x 220 x 11

Descriere completă

Prior work in inductive learning focused on generic§algorithms that sought to reduce complexity. Thus,§simplifying assumptions were made. 1. All data§resides on a single processor, and resides§entirely in main memory;§Clearly in modern organizations today, most data§resides in a distributed§architecture with only small portions being resident§in main memory at each moment. §2. Each datum is considered equally important and uniform§costs are assumed. In real world contexts, different§exemplars frequently have§varying costs.§3. All features are freely acquired with no§computational or monetary§costs. This is unrealistic for many applications,§such as medical diagnosis. Usually, the test for each§feature consumes different costs and cannot be§ignored, i.e., accurate models that only take§advantage of the most expensive features are not§acceptable. §4. Model is computed on the basis of complete§knowledge. A learned hypothesis will§be applied to scenarios that are completely§represented in the training set. This§assumption is more often violated than satisfied.§There are usually new and unknown§patterns that traditional hypotheses will either§ignore or misclassify.

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Cost-sensitive, Scalable and Adaptive Learning Using Ensemble Methods

Theory and Application

Informații despre carte

Descriere completă

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