Machine learning
C4.5: programs for machine learning
C4.5: programs for machine learning
The nature of statistical learning theory
The nature of statistical learning theory
Ordered Estimation of Missing Values
PAKDD '99 Proceedings of the Third Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining
Ensemble Methods in Machine Learning
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
Evaluating probabilistic queries over imprecise data
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Density-based clustering of uncertain data
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Mining Uncertain Data in Low-dimensional Subspace
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 02
OLAP over uncertain and imprecise data
The VLDB Journal — The International Journal on Very Large Data Bases
Efficient Clustering of Uncertain Data
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Dealing with Missing Values in a Probabilistic Decision Tree during Classification
ICDMW '06 Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops
Genre Categorization of Web Pages
ICDMW '07 Proceedings of the Seventh IEEE International Conference on Data Mining Workshops
Targeting Input Data for Acoustic Bird Species Recognition Using Data Mining and HMMs
ICDMW '07 Proceedings of the Seventh IEEE International Conference on Data Mining Workshops
Conceptual Clustering Categorical Data with Uncertainty
ICTAI '07 Proceedings of the 19th IEEE International Conference on Tools with Artificial Intelligence - Volume 01
Approximation algorithms for clustering uncertain data
Proceedings of the twenty-seventh ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
A Rule-Based Classification Algorithm for Uncertain Data
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Mining frequent itemsets from uncertain data
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
Associative classifier for uncertain data
WAIM'10 Proceedings of the 11th international conference on Web-age information management
A discretization algorithm for uncertain data
DEXA'10 Proceedings of the 21st international conference on Database and expert systems applications: Part II
Uncertainty in decision tree classifiers
SUM'10 Proceedings of the 4th international conference on Scalable uncertainty management
Classify uncertain data with decision tree
DASFAA'11 Proceedings of the 16th international conference on Database systems for advanced applications: Part II
UNN: a neural network for uncertain data classification
PAKDD'10 Proceedings of the 14th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part I
Classifier ensemble for uncertain data stream classification
PAKDD'10 Proceedings of the 14th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part I
Mining uncertain data streams using clustering feature decision trees
ADMA'11 Proceedings of the 7th international conference on Advanced Data Mining and Applications - Volume Part II
Cost-sensitive decision tree for uncertain data
ADMA'11 Proceedings of the 7th international conference on Advanced Data Mining and Applications - Volume Part I
Efficient computation of measurements of correlated patterns in uncertain data
ADMA'11 Proceedings of the 7th international conference on Advanced Data Mining and Applications - Volume Part I
Learning very fast decision tree from uncertain data streams with positive and unlabeled samples
Information Sciences: an International Journal
An associative classifier for uncertain datasets
PAKDD'12 Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part I
CD: a coupled discretization algorithm
PAKDD'12 Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part II
Hybrid Bayesian estimation tree learning with discrete and fuzzy labels
Frontiers of Computer Science: Selected Publications from Chinese Universities
EMU: An expectation maximization based approach for clustering uncertain data
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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Decision Tree is a widely used data classification technique. This paper proposes a decision tree based classification method on uncertain data. Data uncertainty is common in emerging applications, such as sensor networks, moving object databases, medical and biological bases. Data uncertainty can be caused by various factors including measurements precision limitation, outdated sources, sensor errors, network latency and transmission problems. In this paper, we enhance the traditional decision tree algorithms and extend measures, including entropy and information gain, considering the uncertain data interval and probability distribution function. Our algorithm can handle both certain and uncertain datasets. The experiments demonstrate the utility and robustness of the proposed algorithm as well as its satisfactory prediction accuracy.