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» A Comparison of Model Aggregation Methods for Regression
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JCP
2006
74views more  JCP 2006»
13 years 7 months ago
Local Boosting of Decision Stumps for Regression and Classification Problems
Numerous data mining problems involve an investigation of associations between features in heterogeneous datasets, where different prediction models can be more suitable for differ...
Sotiris B. Kotsiantis, Dimitris Kanellopoulos, Pan...
ICDM
2010
IEEE
235views Data Mining» more  ICDM 2010»
13 years 4 months ago
Content-Based Methods for Predicting Web-Site Demographic Attributes
Demographic information plays an important role in gaining valuable insights about a web-site's user-base and is used extensively to target online advertisements and promotion...
Santosh Kabbur, Eui-Hong Han, George Karypis
PKDD
2010
Springer
160views Data Mining» more  PKDD 2010»
13 years 6 months ago
Sparse Unsupervised Dimensionality Reduction Algorithms
Abstract. Principal component analysis (PCA) and its dual—principal coordinate analysis (PCO)—are widely applied to unsupervised dimensionality reduction. In this paper, we sho...
Wenjun Dou, Guang Dai, Congfu Xu, Zhihua Zhang
WSC
2004
13 years 9 months ago
Using Simulated Data in Support of Research on Regression Analysis
Using simulated data to develop and study diagnostic tools for data analysis is very beneficial. The user can gain insight about what happens when assumptions are violated since t...
Christopher Michael Hill, Linda C. Malone
ICDM
2005
IEEE
161views Data Mining» more  ICDM 2005»
14 years 1 months ago
Making Logistic Regression a Core Data Mining Tool with TR-IRLS
Binary classification is a core data mining task. For large datasets or real-time applications, desirable classifiers are accurate, fast, and need no parameter tuning. We presen...
Paul Komarek, Andrew W. Moore