Observing Performance of Naive Bayes Classifier on Nursery Dataset

Authors

  • Rajni Bhalla  Lovely Professional University, Phagwara, Punjab, India
  • Amandeep  Lovely Professional University, Phagwara, Punjab, India

DOI:

https://doi.org//10.32628/IJSRSET218410

Keywords:

Natve Bayes, Performance, Classification, Data mining

Abstract

In machine learning, Naive Bayes is a popular technique that is used for classification that is based on the conditional probability of attributes belonging to a label, in which the attribute is selected by select attribute operator in rapid miner. In this paper, the split operator has used that divides the dataset into training and testing. Training is used to train the naïve Bayes and testing is used to evaluate the model. The result shows that this simple model generates a good fit for the nursing dataset. Total accuracy achieved using this method is 87.86% which is not bad.

References

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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2022-05-13

Issue

Volume 9, Issue 3, May-June-2022

Section

Research Articles

License

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Rajni Bhalla, Amandeep, " Observing Performance of Naive Bayes Classifier on Nursery Dataset, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 9, Issue 3, pp.91-95, May-June-2022. Available at doi : https://doi.org/10.32628/IJSRSET218410