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- W3098028340 abstract "Machine learning methods are very widely used in helping human work. Not all data is as we expected. Some data have missing values. Data that has a missing value must be handled first at the pre-processing stage, one of which is by the imputation of the missing value. This study is comparing the imputation method of missing value uses mode and One-Dimensional Na1ve Bayes Classifier (1DNBC) to determine the performance analysis by using Support Vector Machine (SVM) for the prediction of car insurance participation. A better method is seen from the accuracy. Based on the simulation is obtained the same results for imputation using mode and One-Dimensional Na1ve Bayes are 1.00, which when examined further turns out to be the imputation of each missing value with the mode and prediction of imputation with One-Dimensional Na1ve Bayes are the same." @default.
- W3098028340 created "2020-11-23" @default.
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- W3098028340 date "2020-01-01" @default.
- W3098028340 modified "2023-09-26" @default.
- W3098028340 title "Performance analysis of one-dimensional naiïve bayes as a data imputation method for car insurance problems" @default.
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- W3098028340 doi "https://doi.org/10.1063/5.0030542" @default.
- W3098028340 hasPublicationYear "2020" @default.
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