This paper predicts the Diabetes Disease based on Data Mining Techniques of Classification algorithms. Classification algorithm and tools may reduce heavy work on Doctors. In this paper Evaluated as Classification Alg...
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ISBN:
(纸本)9781467382878
This paper predicts the Diabetes Disease based on Data Mining Techniques of Classification algorithms. Classification algorithm and tools may reduce heavy work on Doctors. In this paper Evaluated as Classification algorithms for the Classify of some Diabetes Disease Patient Datasets. Data Mining is one of the main algorithm is Classification. Classification algorithm Examine of the decision tree algorithm, Byes algorithm and Rule based algorithm. These algorithms are evaluate Error Rates and identify of the patients based evolution Function of the measure the accurate results.
Nowadays, with the expanding of database application, every fields have accumulated huge amounts of data including the College students' activities records. These records are very meticulously reflecting the statu...
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Nowadays, with the expanding of database application, every fields have accumulated huge amounts of data including the College students' activities records. These records are very meticulously reflecting the status of the students' learning and life by analysis their relationships using data mining techniques. The traditional methods of choosing Excellent students and Outstanding Class Leader and Postgraduate Recommendation and Poor students is manual manipulation. But, in this paper, we develop a system which brings in data mining techniques with decision tree algorithm and association rules mining algorithm. Through analyzing the data from college student library records and consumption records and student score and psychological test done by the students, this information system can automatically show the results under data mining algorithm.
Money laundering behavior recognition was a process of knowledge discovery in databases (KDD). Data Mining was an important technique of KDD. In this paper, the characteristics of Chinese foreign exchange money launde...
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Money laundering behavior recognition was a process of knowledge discovery in databases (KDD). Data Mining was an important technique of KDD. In this paper, the characteristics of Chinese foreign exchange money laundering activities, and combine decisiontree approach with financial domain knowledge were analyzed. The suitable money laundering transaction recognition strategy and method were chosen. By making full use of the real transaction data to carry on the experiment, useful rules of money laundering were discovered. Experimental results on SAS demonstrated that our algorithm could be extremely useful in money laundering recognition.
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