Estimating Probability Values Based on Naïve Bayes for Fuzzy Random Regression Model
In the process of treating uncertainties of fuzziness and randomness in real regression application, fuzzy random regression was introduced to address the limitation of classical regression which can only fit precise data. However, there is no systematic procedure to identify randomness by means o...
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| 主要な著者: | , , , |
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| フォーマット: | 論文 |
| 言語: | English |
| 出版事項: |
ijacsa
2023
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| 主題: | |
| オンライン･アクセス: | http://eprints.uthm.edu.my/10608/1/J16599_c36a87cfb6ca4c06d67a665909747d79.pdf http://eprints.uthm.edu.my/10608/ |
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| 要約: | In the process of treating uncertainties of fuzziness
and randomness in real regression application, fuzzy random
regression was introduced to address the limitation of classical regression which can only fit precise data. However, there is no systematic procedure to identify randomness by means of probability theories. Besides, the existing model mostly concerned in fuzzy equation without considering the discussion on probability equation though random plays a pivotal role in fuzzy random regression model. Hence, this paper proposed a systematic procedure of Naïve Bayes to estimate the probabilities value to overcome randomness. From the result, it shows that the accuracy of Naïve Bayes model can be improved by considering the probability estimation. |
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