Comparative analysis of machine learning techniques in optimal site selection

Comparative analysis of machine learning techniques in optimal site selection

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023.

Dades bibliogràfiques
Autors principals:	Aurnab, Aukik, Choudhury, Shaktiman, Ruhan, Shoubhick Roy, Rifaiya Abrar, Shikh Muhammad, Hossain Rabbi, S.M. Riyadh
Altres autors:	Khan, Rubayat Ahmed
Format:	Thesis
Idioma:	English
Publicat:	Brac University 2023
Matèries:	Optimal Site Selection (OSS) Comparative analysis Boosting and stacking SVR Random forest XGBoost Ridge regression Lasso regression Elasticnet Convolutional Neural Network (CNN) Ensemble learning VGG16 VGG19 ResNet DenseNet InceptionV3 Root Mean Squared Error (RMSE) Mean Squared Error (MSE) Mean Absolute Error (MAE) Median Absolute Error (MedAE) Max error (ME) Median Absolute Deviation(MAD) Machine learning. Artificial intelligence.
Accés en línia:	http://hdl.handle.net/10361/19150

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