DISummit presentation for the denguehack winners for "best model" and "audience prize"

1. OLIVIER VAN TONGERLOO / NICO VERHEYDEN
DATASCIENTIST - KEYRUS / BIG DATACONSULTANT - RANDSTAD PROFESSIONALS
Data Innovation Summit
March, 30 2017
#DIS2017
Denguehack 2016 winners
“best model” & “audience prize”

2. Olivier Van
Tongerloo
Data scientist
Duke Assam
Data scientist
Nico
Verheyden
Big Data
consultant
Wiljan Cools
Student big
data analytics
Wojciech
Kuberski
Student master
in artificial
intelligence
Kostas
Theodorakos
Software
developer
Ana Cristina
Rosa
Entrepreneur
Our team
The Juniors
DIHub bootcamp Graduates

3. Our challenge
Predict Dengue outbreaks using open data
Why? When? Where?

4. Which features
will predict a
dengue outbreak
Why? When? Where?
Our challenge
Predict Dengue outbreaks using open data

5. Which features
will predict a
dengue outbreak
Why?
Enough time to
take measures to
prevent an
outbreak
When? Where?
Our challenge
Predict Dengue outbreaks using open data

6. Which features
will predict a
dengue outbreak
Why?
Enough time to
take measures to
prevent an
outbreak
Pinpoint a small
enough region to
be able to take
preventive actions
When? Where?
Our challenge
Predict Dengue outbreaks using open data

7. Scalable
Transferable
Reliable
iInformative
Our solution
General prediction model

8. Our model can be extended with other data
and new regions
Scalable
Transferable
Reliable
iInformative
Our solution
General prediction model

9. No region specific data is used
Our model can be extended with other data
and new regions
Scalable
Transferable
Reliable
iInformative
Our solution
General prediction model

10. A prediction window of only 4 weeks is used
to be reliable but still usable
No region specific data is used
Our model can be extended with other data
and new regions
Scalable
Transferable
Reliable
iInformative
Our solution
General prediction model

11. Predictive features are returned by the model
A prediction window of only 4 weeks is used
to be reliable but still usable
No region specific data is used
Our model can be extended with other data
and new regions
Scalable
Transferable
Reliable
iInformative
Our solution
General prediction model

12. Binomial classification using time series
(Focus on Malaysia as most data concerning outbreaks was available from that region)
Our Approach
Technical solution
• Climate data (3 months)
• Confirmed dengue cases
• Data of neighbour province
• Demographics
Data preparation
• logistic regression
• Random forest (best)
Model building
• Test on test data
Model testing

13. True Data Prediction
Our Model
Results

14. • Add more (open) data to refine the model:
• Other countries
• Vegetation
• Lifestock
• Socio-economical data
• Logistics/transportation data
Next steps
Possible improvements

15. THANK YOU!
THE JUNIORS TEAM