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  Browse All Reviews > Computing Methodologies (I) > Pattern Recognition (I.5) > Models (I.5.1) > Statistical (I.5.1...)  
 
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  1-10 of 18 Reviews about "Statistical (I.5.1...)": Date Reviewed
  Cognitive computing and big data analytics
Hurwitz J., Kaufman M., Bowles A., Wiley Publishing, Hoboken, NJ, 2015. 288 pp.  Type: Book (978-1-118896-62-4)

The claim that a system is “cognitive” can mean one of two very different things. For a half-century, the artificial intelligence (AI) research community has used the term to refer to approaches that mimic human mec...

Oct 5 2015
  Bayesian nonlinear principal component analysis using random fields
Lian H. IEEE Transactions on Pattern Analysis and Machine Intelligence 31(4): 749-754, 2009.  Type: Article

The complexity of data involved in business and scientific applications has increased tremendously recently, and this trend appears to be continuing. Thus, there is an urgent need for tools that can analyze and characterize large high-...

Aug 19 2009
  The minimum description length principle
Grünwald P., The MIT Press, 2007. 504 pp.  Type: Book (9780262072816), Reviews: (2 of 2)

Seven-hundred years ago, a Franciscan logician from the English village of Ockham formulated the philosophical principle that has come to be known as “Ockham’s [or Occam’s] Razor: Entities must not be mult...

Mar 24 2009
  Bayesian core: a practical approach to computational Bayesian statistics
Marin J., Robert C., Springer Publishing Company, Incorporated, 2007. 255 pp.  Type: Book (9780387389837)

This book’s title captures its focus. It is a textbook covering the core statistical models from both a Bayesian viewpoint and a computational viewpoint. The book’s structure is similar for each core model covered. ...

Dec 3 2008
  The minimum description length principle
Grünwald P., The MIT Press, 2007. 504 pp.  Type: Book (9780262072816), Reviews: (1 of 2)

Minimum description length (MDL) is an information-theoretic method for inductive inference. MDL is related to, but also quite different from, the older notion of minimum message length (MML). This book is a detailed and comprehensive ...

Dec 5 2007
  A statistical approach to neural networks for pattern recognition (Wiley Series in Computational Statistics)
Dunne R., Wiley-Interscience, 2007. 288 pp.  Type: Book (9780471741084)

A statistical treatment of a common neural net structure, the multilayer perceptron, in a language that is familiar to working statisticians is addressed in this book. Several questions arise when statisticians are confronted with such...

Nov 6 2007
  Rule extraction from support vector machines: a sequential covering approach
Barakat N., Bradley A. IEEE Transactions on Knowledge and Data Engineering 19(6): 729-741, 2007.  Type: Article

Interest in the combination of statistical pattern recognition learning techniques and rule-based learning has grown in the last few years, and it appears as if it will be an important field in the future. In this paper, a novel system...

Sep 7 2007
  Stock market prediction with multiple classifiers
Qian B., Rasheed K. Applied Intelligence 26(1): 25-33, 2007.  Type: Article

After reading this work, I finally understood what stock prices are and how stock market predictions can be built. The paper highlights a bridge existing between machine learning and economics. Basically, the authors introduce a way to...

Jun 7 2007
  Correlation pattern recognition
Kumar B., Mahalanobis A., Juday R., Cambridge University Press, New York, NY, 2005. 402 pp.  Type: Book (9780521571036)

Pattern recognition in images has many applications, from scanning bar codes to identifying human faces. Feature-based recognition methods examine images piecewise, and make decisions based on comparing features and their relationships...

Feb 21 2007
  Kernel density classification and boosting: an L2 analysis
Marzio M., Taylor C. Statistics and Computing 15(2): 113-123, 2005.  Type: Article

Boosting is a new learning technique that has become very attractive to many researchers involved in the areas of machine learning and statistical pattern recognition. The general idea of boosting is to develop the classifier team incr...

Apr 28 2006
 
 
 
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