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| Titel: |
An Efficient Implementation of Re-Sampling Technique for High Performance Multiple Classifier Systems |
| Auteur: |
S.Sathiyabama K. Thyagarajah D.Ayyamuthukumar |
| Verschenen in: |
Journal of computer science |
| Paginering: | Jaargang 3 (2007) nr. 4 pagina's 195-198 |
| Jaar: |
2007 |
| Inhoud: |
Due to the large size of the database, the entire training dataset could not be used toconstruct the classifiers. One popular solution is to separate stream data into chunks, learn a baseclassifier from each chunk and then integrate all base classifiers to form Multiple classifier system(MCS). Sometimes this data streams does not include all the classes in its equal proportion as in theentire training data set. So we have newly introduced a method of Re-Sampling based on the statisticalvalue of the class attribute. In the Proposed Method, the probability of occurrences of every class forthe entire training data set have been estimated. Based on the probability, thresholds have been fixedfor all the classes. When the data set have been selected randomly, the probabilities of the classes havebeen checked against the thresholds. The sample, which satisfies all the thresholds, is allowed toconstruct the Model. Otherwise, Re-sampling is performed and the process is repeated until the samplesatisfies all the thresholds for the classes. The proposed method yields more accuracy than the onewhich does not have threshold on classes in the random samples. We have also compared the accuracyof different classifiers. Experimental results and comparative studies demonstrate the efficiency andefficacy of our method. |
| Uitgever: |
Science Publications (provided by DOAJ) |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
Details van artikel 13 van 49 gevonden artikelen
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