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» The Problem of Missing Values in Decision Tree Grafting
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AUSAI
1998
Springer
13 years 11 months ago
The Problem of Missing Values in Decision Tree Grafting
Decision tree grafting adds nodes to inferred decision trees. Previous research has demonstrated that appropriate grafting techniques can improve predictive accuracy across a wide ...
Geoffrey I. Webb
DIS
2004
Springer
13 years 11 months ago
Generating AVTs Using GA for Learning Decision Tree Classifiers with Missing Data
Abstract. Attribute value taxonomies (AVTs) have been used to perform AVT-guided decision tree learning on partially or totally missing data. In many cases, user-supplied AVTs are ...
Jinu Joo, Jun Zhang 0002, Jihoon Yang, Vasant Hona...
DKE
2008
98views more  DKE 2008»
13 years 7 months ago
Privacy-preserving imputation of missing data
Handling missing data is a critical step to ensuring good results in data mining. Like most data mining algorithms, existing privacy-preserving data mining algorithms assume data ...
Geetha Jagannathan, Rebecca N. Wright
ICDM
2006
IEEE
169views Data Mining» more  ICDM 2006»
14 years 1 months ago
Privacy-Preserving Data Imputation
In this paper, we investigate privacy-preserving data imputation on distributed databases. We present a privacypreserving protocol for filling in missing values using a lazy deci...
Geetha Jagannathan, Rebecca N. Wright
PKDD
1999
Springer
272views Data Mining» more  PKDD 1999»
13 years 11 months ago
Handling Missing Data in Trees: Surrogate Splits or Statistical Imputation
Abstract. In many applications of data mining a - sometimes considerable - part of the data values is missing. This may occur because the data values were simply never entered into...
A. J. Feelders