Classification of Environmental Attitudes with Artificial Intelligence Algorithms - KOKLU, Nigmet; SULAK, Suleyman Alpaslan (Intelligent Methods In Engineering Sciences, 2024)
The study aims to examine people’s attitudes towards the environment. Environmental education provides the necessary awareness to effectively address environmental issues. It is stated that attitudes towards the environment are very important and negative attitudes can worsen environmental problems. For this purpose, a dataset was obtained by using a scale consisting of 37 variables to a participant group consisting of 384 people. With this dataset, attitudes towards the environment have been analyzed using various classification algorithms. Logistic Regression (LR), Support Vector Machine (SVM) and Decision Tree (DT) models were used in the research. The LR, SVM, and DT models achieved 94.53%, 92.96%, and 82.55% classification success, respectively It is seen that the classification achievements of the models are at an acceptable level compared to the literature. As a result, the research sheds light on people’s attitudes towards the environment through classification processes. Despite the acceptable classification achievements, alternative artificial Intelligence approaches can also be used to improve performance.