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Journals / International Journal of Intelligent Systems and Applications in Engineering / 2017 / Cilt: 5 - Sayı: 2

Comparison of Classification Techniques on Energy Efficiency Dataset

AHMET TOPRAK
NİĞMET KÖKLÜ
AYŞEGÜL TOPRAK
RECAİ ÖZCAN
Pages
4188–8652
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

When comparing the performances of algorithms it’s been found that Rotation Forest has highest accuracy whereas Dagging had the worst accuracy

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The definition of the data mining can be told as to extract information or knowledge from large volumes of data.
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Key Findings & Data:In this study 10 different Data Mining methods namely Bagging, Decorate, Rotation Forest, J48, NNge, K-Star, Naïve Bayes, Dagging, Bayes Net and JRip classification methods were applied on energy efficiency dataset that were taken from UCI Machine Learning Repository.
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Conclusion & Impact:When comparing the performances of algorithms it’s been found that Rotation Forest has highest accuracy whereas Dagging had the worst accuracy
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

The definition of the data mining can be told as to extract information or knowledge from large volumes of data. Statistical and machine learning techniques are used for the determination of the models to be used for data mining predictions. Today, data mining is used in many different areas such as science and engineering, health, commerce, shopping, banking and finance, education and internet. This study make use of WEKA (Waikato Environment for Knowledge Analysis) to compare the different classification techniques on energy efficiency datasets. In this study 10 different Data Mining methods namely Bagging, Decorate, Rotation Forest, J48, NNge, K-Star, Naïve Bayes, Dagging, Bayes Net and JRip classification methods were applied on energy efficiency dataset that were taken from UCI Machine Learning Repository. When comparing the performances of algorithms it’s been found that Rotation Forest has highest accuracy whereas Dagging had the worst accuracy

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Cite This Article

TOPRAK, A., KÖKLÜ, N., TOPRAK, A., ÖZCAN, R. (2017). Comparison of Classification Techniques on Energy Efficiency Dataset. International Journal of Intelligent Systems and Applications in Engineering, Cilt: 5 - Sayı: 2, 4188–8652. https://ajindex.com/articles/210238

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