Author: Mihir Mehta; Juxihong Julaiti; Paul Griffin; Soundar Kumara
Title: Early Stage Prediction of US County Vulnerability to the COVID-19 Pandemic Document date: 2020_4_11
ID: 901ghexi_19
Snippet: In order to predict COVID-19 outcomes, we divided the problem into three stages. In the first stage, we formulated a binary classification problem that included both positive and negative instances. We developed an XGBoost 48 classifier model to learn from the data. We divided the dataset into training and testing in 80-20 proportions for each class. We tuned the hyperparameters of the model using the Hyopt package......
Document: In order to predict COVID-19 outcomes, we divided the problem into three stages. In the first stage, we formulated a binary classification problem that included both positive and negative instances. We developed an XGBoost 48 classifier model to learn from the data. We divided the dataset into training and testing in 80-20 proportions for each class. We tuned the hyperparameters of the model using the Hyopt package.
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