Classification of Imbalanced Medical Data Efficiently Using Multiclass SVM and Genetic Algorithm
نویسنده
چکیده
We focused on developing efficient support vector machine based on genetic algorithm for multiclass classification from large of collection imbalanced data. And gives well sorted data. Many years ago, the scientific community is concerned about how to increase the accuracy of different classification methods, and major achievements have been made so far. Hadoop and MapReduce are used to handle these large volumes of variable size data. In proposed system we can take sufficient .csv file as inputs & we apply variance algorithm & generate expected results. Classification is method to perform on poorly & minority class examples when the dataset is extremely imbalanced.
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