Handling Missing Value in Decision Tree Algorithm
نویسندگان
چکیده
منابع مشابه
A Decision Tree-based Missing Value Imputation Technique for Data Pre-processing
Data pre-processing plays a vital role in data mining for ensuring good quality of data. In general data preprocessing tasks include imputation of missing values, identification of outliers, smoothening out of noisy data and correction of inconsistent data. In this paper, we present an efficient missing value imputation technique called DMI, which makes use of a decision tree and expectation ma...
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Decision tree grafting adds nodes to inferred decision trees. Previous research has demonstrated that appropriate grafting techniques can improve predictive accuracy across a wide cross-selection of domains. However, previous decision tree grafting systems are demonstrated to have a serious deeciency for some data sets containing missing values. This problem arises due to the method for handlin...
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Decision-tree algorithms provide one of the most popular methodologies for symbolic knowledge acquisition. The resulting knowledge, a symbolic decision tree along with a simple inference mechanism, has been praised for comprehensibility. The most comprehensible decision trees have been designed for perfect symbolic data. Classical crisp decision trees (DT) are widely applied to classification t...
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ژورنال
عنوان ژورنال: International Journal of Computer Applications
سال: 2013
ISSN: 0975-8887
DOI: 10.5120/12023-8063