Predictions
ID
Lang
Model name
Repository
Description
LSTM model for Infodengue Sprint
Predictions for 2023 in RO using the comb_att_n architecture
LSTM model for Infodengue Sprint
Predictions for 2023 in SP using the baseline architecture
Temp-SPI Interaction Model
Validation test 2 for three-way interaction model (AM)
Random Forest model with uncertainty computed with conformal prediction
Forecast de novos casos para o geocode 2704302 entre 2022-01-01 e 2023-01-01 usando apenas os dados de 2704302 como input
Deep learning model using BI-LSTM Layers
Forecast de novos casos para o geocode 2211001 entre 2022-01-01 e 2023-01-01 usando apenas os dados do geocode 2211001
LaCiD/UFRN
Dengue predictions for MA using Validation Test 1
LSTM model for Infodengue Sprint
Predictions for 2024 in AL using the baseline architecture
Deep learning model using BI-LSTM Layers
Forecast de novos casos para o geocode 2408102 entre 2022-01-01 e 2023-01-01 usando apenas os dados do geocode 2408102
Random Forest model with uncertainty computed with conformal prediction
Forecast de novos casos para o geocode 2507507 entre 2022-01-01 e 2023-01-01 usando apenas os dados de 2507507 como input
LSTM model for Infodengue Sprint
Predictions for 2024 in RN using the baseline architecture
LaCiD/UFRN
Dengue predictions for GO using Validation Test 1
LSTM model for Infodengue Sprint
Predictions for 2024 in TO using the baseline architecture
LSTM model for Infodengue Sprint
Predictions for 2024 in PI using the baseline architecture
Random Forest model with uncertainty computed with conformal prediction
Forecast de novos casos para o geocode 2927408 entre 2022-01-01 e 2023-01-01 usando apenas os dados de 2927408 como input
Univariate neural prophet model
Forecast de novos casos para o geocode 2304400 entre 2022-01-01 e 2023-07-02
Deep learning model using BI-LSTM Layers
Forecast de novos casos para o geocode 2704302 entre 2022-01-01 e 2023-01-01 usando apenas os dados do geocode e das cidades clusterizadas com ele
LSTM model for Infodengue Sprint
Predictions for 2023 in AL using the baseline architecture
Deep learning model using BI-LSTM Layers
Forecast de novos casos para o geocode 2111300 entre 2022-01-01 e 2023-01-01 usando apenas os dados do geocode e das cidades clusterizadas com ele
LSTM model for Infodengue Sprint
Predictions for 2023 in PI using the baseline architecture
Random Forest model with uncertainty computed with conformal prediction
Forecast de novos casos para o geocode 2408102 entre 2022-01-01 e 2023-01-01 usando apenas os dados de todos as cidades clusterizadas com 2408102 como input
Random Forest model with uncertainty computed with conformal prediction
Forecast de novos casos para o geocode 2927408 entre 2022-01-01 e 2023-01-01 usando apenas os dados de todos as cidades clusterizadas com 2927408 como input
Random Forest model with uncertainty computed with conformal prediction
Forecast de novos casos para o geocode 2611606 entre 2022-01-01 e 2023-01-01 usando apenas os dados de todos as cidades clusterizadas com 2611606 como input
LSTM model for Infodengue Sprint
Predictions for 2023 in DF using the att_3 architecture
Deep learning model using BI-LSTM Layers
Forecast de novos casos para o geocode 2304400 entre 2022-01-01 e 2023-01-01 usando apenas os dados do geocode e das cidades clusterizadas com ele
2569 predictions
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