Thus, this study applied data mining technique to identify the hidden information that affects the ... Surenah,Sedek 被引量: 0发表: 2008年 Topics in Bayesian and computational statistics. This thesis presents statistical methods for several problems in Bayesian and computational statistics. The ...
Statistical methods in genetics In recent years, a very large variety of statistical methodologies, at various levels of complexity, have been put forward to analyse genotype data and det... M Giovanni - 《Briefings in Bioinformatics》 被引量: 83发表: 2006年 Statistical, Computational and Visualiz...
The outlier detection in the field of data mining and Knowledge Discovering from Data (KDD) is capturing special interest due to its benefits. It can be applied in the financial area; because the obtained data patterns can help finding possible frauds and user errors. Therefore, it is essential...
In this study two categories of techniques :Statistical techniques and data mining technique ,one methods from each technique is considered for comparative study ,these are decision tree technique C5.0 and support vector machine (SVM) applied on widely used intrusion data i.e. NSL-KDD data set ...
In this study, the gene expressions of breast cancer tumors are investigated and the performance of several popular classification methods, including decision tree, logistic regression, linear discriminant analysis, and k-nearest neighbor are compared. The results show that certain genes are significantly...
Using cluster analysis for data mining in educational technology research Cluster analysis is a group of statistical methods that has great potential for analyzing the vast amounts of web server-log data to understand student lea... PD Antonenko,S Toy,DS Niederhauser - 《Educational Technology Res...
Solve data analysis problems associated with massive, complex datasets Develop innovative statistical approaches, machine learning algorithms, or methods integrating ideas across disciplines, e.g., statistics, computer science, electrical engineering, operation research. Formulate and solve high-impact real-wo...
novel statistical and/or machine learning methods and theory, and state-of-the-art applications with high impact. Of special interest are articles that describe innovative analytical techniques, and discuss their application to real problems, in such a way that they are accessible and beneficial to...
There is also a chapter on methods for ``wide'' data (p bigger than n), including multiple testing and false discovery rates. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and ...
including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorization, and spectral clustering. There is also a chapter on methods for "wide" data (p bigger than n), including multiple testing and fal...