Dergiler / Advances in Artificial Intelligence Research / 2026 / Cilt: 2 Sayı: 1

Classification of Iris Flower by Random Forest Algorithm

Hilmi Bayrakçı(ISPARTA UYGULAMALI BİLİMLER ÜNİVERSİTESİ, TEKNOLOJİ FAKÜLTESİ)0000-0001-5064-7310
Abdullah Burak Keşkekçi(ISPARTA UYGULAMALI BİLİMLER ÜNİVERSİTESİ TEKNOLOJİ FAKÜLTESİ)0000-0001-8432-7470
Recep Arslan(ISPARTA UYGULAMALI BİLİMLER ÜNİVERSİTESİ TEKNOLOJİ FAKÜLTESİ)0000-0002-0930-505X
Sayfa
7–14
Yayın Tarihi
2022-02-16
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Yapay Zeka Hızlı Bakış & Çıkarımlar

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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

The random forest algorithm was the most successful among the trained algorithms with an accuracy rate of 97%.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:With the introduction of artificial intelligence into our lives, artificial intelligence researches and applications in different fields such as agriculture, health, military and engineering applications have become very popular iris flower was classified using the popular Random Forest, support vector machine and Artificial neural network machine learning classifiers with high accuracy rates.
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Temel Bulgular & Veri:As a result of the classification, the performance of the trained models was evaluated according to the confusion matrix, sensitivity, specificity, accuracy, F1 score, ROC curve and AUC evaluation criteria.
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Sonuç & Katkı:The random forest algorithm was the most successful among the trained algorithms with an accuracy rate of 97%.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:random forest · iris dataset · classification

Abstract

With the introduction of artificial intelligence into our lives, artificial intelligence researches and applications in different fields such as agriculture, health, military and engineering applications have become very popular iris flower was classified using the popular Random Forest, support vector machine and Artificial neural network machine learning classifiers with high accuracy rates. As a result of the classification, the performance of the trained models was evaluated according to the confusion matrix, sensitivity, specificity, accuracy, F1 score, ROC curve and AUC evaluation criteria. The random forest algorithm was the most successful among the trained algorithms with an accuracy rate of 97%.

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Bu Makaleye Atıf Yap

Bayrakçı, H., Keşkekçi, A. B., Arslan, R. (2022). Classification of Iris Flower by Random Forest Algorithm. Advances in Artificial Intelligence Research, Cilt: 2 Sayı: 1, 7–14. https://doi.org/10.54569/aair.1018444

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