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In this section there are notebooks for dengue modelling.
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February 12, 2024 | 09:14:00 +01:00
Raphael Saldanha
Model simplified reference dataset
February 12, 2024 | 09:10:51 +01:00
Raphael Saldanha
Exploratory Data Analysis
Variable type: character
February 8, 2024 | 11:57:38 +01:00
Raphael Saldanha
Dengue case classification
by symptoms and clinical condition
The objective of this notebook is to train a model to…
February 8, 2024 | 10:54:45 +01:00
Raphael Saldanha
Multivariate clustering, all data model
This notebooks aims to reproduce the methodology of the paper submitted to the SBD2023 conference, implementing the global and subset modelling with a multivariate approach.
February 1, 2024 | 09:05:51 +01:00
Raphael Saldanha
Denque and weather lags
This notebook…
January 25, 2024 | 15:18:06 +01:00
Raphael Saldanha
Time series features clustering
This notebooks aims to implement the global and subset modelling, adopting a clustering strategy based on time series features extraction, with the
{tsfeatures}
package.
December 1, 2023 | 09:07:18 +01:00
Raphael Saldanha
SBD clustering
This notebooks aims to reproduce the metodology of the paper submitted to the SBD2023 conference, implementing the global and subset modelling.
December 1, 2023 | 09:07:18 +01:00
Raphael Saldanha
Regression task
This notebook models the relationship between dengue cases and weather variables using the nominal value of dengue cases.
December 1, 2023 | 09:07:18 +01:00
Raphael Saldanha
Dengue case classification
by symptoms and clinical condition
The objective of this notebook is to predict a dengue suspected case based on its symptoms, clinical conditions and other patient related variables.
December 1, 2023 | 09:07:18 +01:00
Raphael Saldanha
Classification task
This notebook models the relationship between dengue cases and weather variables using a classification of dengue cases as outbreak level (anomaly) or base level.
December 1, 2023 | 09:07:18 +01:00
Raphael Saldanha
Time series features clustering, with robust sparse k-means
This notebooks aims to implement the global and subset modelling, adopting a clustering strategy based on time series features extraction, with the
{tsfeatures}
package.
December 1, 2023 | 09:07:18 +01:00
Raphael Saldanha
Multivariate clustering, climate model
This notebooks aims to reproduce the methodology of the paper submitted to the SBD2023 conference, implementing the global and subset modelling with a multivariate approach.
December 1, 2023 | 09:07:18 +01:00
Raphael Saldanha
Global and subset models workflow
December 1, 2023 | 09:07:18 +01:00
Raphael Saldanha
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Climate variables multivariate clustering
Denque and weather lags
