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What is Curse of Dimensionality

Chapter 73
Encyclopedia of Business Analytics and Optimization
As the dimensionality increases the available data becomes sparse and requires large amount of data for any learning method that requires statistical significance to produce a reliable result.
Published in Chapter:
Efficient High Dimensional Data Classification
Hari Seetha (VIT University, Vellore, India) and M.Narasimha Murty (Indian Institute of Science, Bangalore, India)
Copyright: © 2014 |Pages: 8
DOI: 10.4018/978-1-4666-5202-6.ch073
Full Text Chapter Download: US $37.50 Add to Cart
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Chapter 7
Causal Feature Selection
Refers to the problem when analyzing data in high dimensional space that does not occur in low dimensional.
Published in Chapter: Causal Feature Selection; From: Integration Challenges for Analytics, Business Intelligence, and Data Mining
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Chapter 159
Mobile Robots Navigation, Mapping, and Localization Part II
This term was first used by Richard Bellman. It refers to the problem of exponential increase in volume associated with adding extra dimensions to a mathematical space.
Published in Chapter: Mobile Robots Navigation, Mapping, and Localization Part II; From: Encyclopedia of Artificial Intelligence
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Chapter 17
Deep-Auto Encoders for Detecting Credit Card Fraud
Difficulty in analyzing the dataset becomes increasingly complicated as the number of dimensions rises. It is known as the curse of dimensionality.
Published in Chapter: Deep-Auto Encoders for Detecting Credit Card Fraud; From: Handbook of Research on the Significance of Forensic Accounting Techniques in Corporate Governance
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Chapter 100
Functional Dimension Reduction for Chemometrics
A theoretical result in machine learning that states that the lower bound of error that an adaptive machine can achieve increases with data dimension. Thus performance will degrade as data dimension grows.
Published in Chapter: Functional Dimension Reduction for Chemometrics; From: Encyclopedia of Artificial Intelligence
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Chapter 10
AI Methods for Analyzing Microarray Data
A situation where the number of features (genes) is much larger than the number of instances (biological samples) which is known in statistics as p >> n problem.
Published in Chapter: AI Methods for Analyzing Microarray Data; From: Encyclopedia of Artificial Intelligence
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Chapter 239
Web Page Classification Using MDAWkNN
When processing Big Data of huge dimensions, much of the objects seem to be sparse after they are pre-processed. They are also dissimilar in many ways which prevents common data organization strategies from being efficient. This problem faced by the statistics community is known as curse of dimensionality.
Published in Chapter: Web Page Classification Using MDAWkNN; From: Encyclopedia of Business Analytics and Optimization
Full Text Chapter Download: US $37.50 Add to Cart
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