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- 3Pouria Ramazi
- 3Russell Greiner
- 2Mélodie Kunegel-Lion
- 1Arezoo Haratian
- 1David Wishart
- 3Machine learning
- 1Automatic learning
- 1Bayesian network
- 1COVID-19
- 1Epidemiology
- 1Future infestations
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2021-01-01
Arezoo Haratian, Hadi Fazelinia, Zeinab Maleki, Pouria Ramazi, Hao Wang, Mark A. Lewis, Russell Greiner, David Wishart
This dataset provides information related to the outbreak of COVID-19 disease in the United States, including data from each of 3142 US counties from the beginning of the outbreak (January 2020) until June 2021. This data is collected from many public online databases and includes the...
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2021-01-05
Pouria Ramazi, Mélodie Kunegel-Lion, Russell Greiner, Mark A. Lewis
Although ecological models used to make predictions from underlying covariates have a record of success, they also suffer from limitations. They are typically unable to make predictions when the value of one or more covariates is missing during the testing. Missing values can be estimated but...
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2021-10-01
Pouria Ramazi, Mélodie Kunegel-Lion, Russell Greiner, Mark A. Lewis
Planning forest management relies on predicting insect outbreaks such as mountain pine beetle, particularly in the intermediate‐term future, e.g., 5‐year. Machine‐learning algorithms are potential solutions to this challenging problem due to their many successes across a variety of prediction...