Chapter 1: Statistical Data Mining, Wegman, Edward J. and Solka, Jeffrey L.
Chapter 2: From Data Mining to Knowledge Mining, Kaufman, Kenneth A. and Michalski, Ryszard S.
Chapter 3: Mining Computer Security Data, Marchette, David J.
Chapter 4: Data Mining of Text Files, Martinez, Angel R.
Chapter 5: Text Data Mining with Minimal Spanning Trees, Solka, Jeffrey L., Bryant, Avory C., and Wegman, Edward J.
Chapter 6: Information Hiding: Steganography and Steganalysis, Duric, Zoran, Jacobs, Michael, and Jajodia, Sushil
Chapter 7: Canonical Variate Analysis and Related Methods for Reduction of Dimensionality and Graphical Representation, Rao, C. Radhakrishna
Chapter 8: Pattern Recognition, Hand, David J.
Chapter 9: Multivariate Density Estimation, Scott, David J. and Sain, Stephan R.
Chapter 10: Multivariate Outlier Detection and Robustness, Hubert, Mia, Rousseeuw, Peter J., and Van Aelst, Stefan
Chapter 11: Classification and Regression Trees, Bagging, and Boosting, Sutton, Clifton D.
Chapter 12: Fast Algorithms for Classification Using Class Cover Catch Digraphs, Marchette, David J., Wegman, Edward J., and Priebe, Carey E.
Chapter 13: On Genetic Algorithms and their Applications, Said, Yasmin
Chapter 14: Computational Methods for High-Dimensional Rotations in Data Visualization, Buja, Andreas, Cook, Dianne, Asimov, Daniel, and Hurley, Catherine
Chapter 15: Some Recent Graphics Templates and Software for Showing Statistical Summaries, Carr, Daniel B.
Chapter 16: Interactive Statistical Graphics: The Paradigm of Linked Views, Wilhelm, Adalbert
Chapter 17: Data Visualization and Virtual Reality, Chen, Jim X.
Data Mining and Data Visualization focuses on dealing with large-scale data, a field commonly referred to as data mining. The book is divided into three sections. The first deals with an introduction to statistical aspects of data mining and machine learning and includes applications to text analysis, computer intrusion detection, and hiding of information in digital files. The second section focuses on a variety of statistical methodologies that have proven to be effective in data mining applications. These include clustering, classification, multivariate density estimation, tree-based methods, pattern recognition, outlier detection, genetic algorithms, and dimensionality reduction. The third section focuses on data visualization and covers issues of visualization of high-dimensional data, novel graphical techniques with a focus on human factors, interactive graphics, and data visualization using virtual reality. This book represents a thorough cross section of internationally renowned thinkers who are inventing methods for dealing with a new data paradigm.
- Distinguished contributors who are international experts in aspects of data mining
- Includes data mining approaches to non-numerical data mining including text data, Internet traffic data, and geographic data
- Highly topical discussions reflecting current thinking on contemporary technical issues, e.g. streaming data
- Discusses taxonomy of dataset sizes, computational complexity, and scalability usually ignored in most discussions
- Thorough discussion of data visualization issues blending statistical, human factors, and computational insights
Statisticians, Data Mining/Database People and Computer Graphics
- No. of pages:
- © North Holland 2005
- 2nd May 2005
- North Holland
- eBook ISBN:
- Hardcover ISBN:
Professor C. R. Rao, born in India, is one of this century's foremost statisticians, and received his education in statistics at the Indian Statistical Institute (ISI), Calcutta. He is Emeritus Holder of the Eberly Family Chair in Statistics at Penn State and Director of the Center for Multivariate Analysis. He has long been recognized as one of the world's top statisticians, and has been awarded 34 honorary doctorates from universities in 19 countries spanning 6 continents. His research has influenced not only statistics, but also the physical, social and natural sciences and engineering.
In 2011 he was recipient of the Royal Statistical Society's Guy Medal in Gold which is awarded triennially to those "who are judged to have merited a signal mark of distinction by reason of their innovative contributions to the theory or application of statistics". It can be awarded both to fellows (members) of the Society and to non-fellows. Since its inception 120 years ago the Gold Medal has been awarded to 34 distinguished statisticians. The first medal was awarded to Charles Booth in 1892. Only two statisticians, H. Cramer (Norwegian) and J. Neyman (Polish), outside Great Britain were awarded the Gold medal and C. R. Rao is the first non-European and non-American to receive the award.
Other awards he has received are the Gold Medal of Calcutta University, Wilks Medal of the American Statistical Association, Wilks Army Medal, Guy Medal in Silver of the Royal Statistical Society (UK), Megnadh Saha Medal and Srinivasa Ramanujan Medal of the Indian National Science Academy, J.C.Bose Gold Medal of Bose Institute and Mahalanobis Centenary Gold Medal of the Indian Science Congress, the Bhatnagar award of the Council of Scientific and Industrial Research, India and the Government of India honored him with the second highest civilian award, Padma Vibhushan, for “outstanding contributions to Science and Engineering / Statistics”, and also instituted a cash award in honor of C R Rao, “to be given once in two years to a young statistician for work done during the preceding 3 years in any field of statistics”.
For his outstanding achievements Rao has been honored with the establishment of an institute named after him, C.R.Rao Advanced Institute for Mathematics, Statistics and Computer Science, in the campus of the University of Hyderabad, India.
The Pennsylvania State University, University Park, PA, USA