I am doing the project on decision tree for uncertain data.can you please tell me the future enhancements to this paper. ....etc

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Abstract

Traditional decision tree classifiers work with data whose values are known and precise. We extend such classifiers to handle data with uncertain information. Value uncertainty arises in many applications during the data collection process. Example sources of uncertainty include measurement/quantization errors, data staleness, and multiple repeated measurements. With uncertainty, the value of a data item is often represented not by one single value, but by multiple values forming a probability distribution. Rather than abstracting unc ....etc

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Classification is a classical problem in machine learning
and data mining. Given a set of training data tuples, each
having a class label and being represented by a feature vector,
the task is to algorithmically build a model that predicts
the class label of an unseen test tuple based on the tuple s
feature vector. One of the most popular classification models
is the decision tree model. Decisions trees are popular because
they are practical and easy to understand. Rules can also be
extracted from decision trees easily. Many algorithms ....etc

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Abstract
Efficiency and scalability are fundamental issues concerning data mining in large databases. Although classification has been studied extensively, few of the known methods take serious consideration of efficient induction in large databases and the analysis of data at multiple abstraction levels. The paper addresses the efficiency and scalability issues by proposing a data classification method which integrates attribute oriented induction, relevance analysis, and the induction of decision trees. Such an integration leads to efficient ....etc

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to get information about the topic privacy preserving decision tree learning using unrealized data sets related topic refer the page link bellow

http://seminarsprojects.net/Thread-privacy-preserving-decision-tree-learning-using-unrealized-data-sets?pid=63305&mode=threaded ....etc

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Data Warehouses, Decision Support and Data Mining

A Data Warehouse is a subject-oriented,integrated,time-variant,non-volatile collection of data used in support of management decision making processes.

Subject-Oriented:-
The data warehouse is organized around the key subjects (or high-level entities) of the enterprise.

Major subjects include
a) Customers
b) Patients
c) Students
d) Products
e) Etc.

Data support :-

Stored collection of diverse data
A solution to data integration problem
Single repository of information
Sub ....etc

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what are the distributed based algorithms used in the decision ....etc

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helloo i am sandhya Prasad. I belong to jharkhand,i have completed b.com from vinobha bhave univ.,10th from cbse board and 12th from jharkhand univ.,and now i am persuing mca from rajhasthan college of engineering with aggrigate 69% marks.



i want source code for decision tree for uncertain data
please send source code for decision tree for uncertain data. ....etc

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to get information about the topic privacy preserving decision tree learning using unrealized data sets 2012 full report refer the page link bellow

http://seminarsprojects.net/Thread-privacy-preserving-decision-tree-learning-using-unrealized-data-sets?pid=63305&mode=threaded ....etc

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I need some project details for the topicPrivacy preserving decision tree for uncertain data in dotnet pls assist me ....etc

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