Implemented 9 models (Logistic Regression, KNN, Penalized Logistic Regression (elastic net penalty), Naïve Bayes, Random Forest, Boosted Trees, LDA, QDA, and SVM) to classify image pixels to identify potential makeshift shelters based on RGB color codes.
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Implemented 9 models (Logistic Regression, KNN, Penalized Logistic Regression (elastic net penalty), Naïve Bayes, Random Forest, Boosted Trees, LDA, QDA, and SVM) to classify image pixels to identify potential makeshift shelters based on RGB color codes.
an-izq/Disaster-Relief-Project
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Implemented 9 models (Logistic Regression, KNN, Penalized Logistic Regression (elastic net penalty), Naïve Bayes, Random Forest, Boosted Trees, LDA, QDA, and SVM) to classify image pixels to identify potential makeshift shelters based on RGB color codes.
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