Analyzing Machine learning Algorithm for Predicting an Accuracy of Meteorological Data

Authors

  • Manikandan M Dept. of Computer Science, Marudupandiyar College, Thanjavur, Tamil Nadu, India
  • Mala R Dept. of Computer Science, Alagappa University College, Paramakudi, Tamil Nadu, India

DOI:

https://doi.org/10.26438/ijcse/v6i10.895899

Keywords:

Randon Forest, C4.5, C4.5 with Bootstrap Algorithm, Meterological Data, Accurac, Time efficiency

Abstract

Meteorological data analysis in the form of data mining is concerned to predict the knowledge of weather condition. To make an accurate prediction is one of the challenging of meteorologist to survey the weather condition efficiently. Decision tree algorithms are suitable for analyzing the data of meteorological behavior. By evaluates three algorithm of decision tree such as Random Forest, C4.5, C4.5 with Bootstrap aggregation, to analyse the time efficiency and accuracy of classification. These accuracy of algorithm when it operates on trained weather data of selected location. Those locations are selected through monsoon condition based on India country

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Published

2025-11-17
CITATION
DOI: 10.26438/ijcse/v6i10.895899
Published: 2025-11-17

How to Cite

[1]
M. Manikandan and R. Mala, “Analyzing Machine learning Algorithm for Predicting an Accuracy of Meteorological Data”, Int. J. Comp. Sci. Eng., vol. 6, no. 10, pp. 896–999, Nov. 2025.

Issue

Vol. 6 No. 10 (2018): IJCSE October Edition

Section

Research Article

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