Uber Nairobi Ambulance Perambulation Challenge
$6,000 USD
Can you use ML to create an optimised ambulance deployment strategy in Nairobi?
1029 data scientists enrolled, 331 on the leaderboard
ConstructionTransportationHealthPredictionStructuredLocation
Kenya
17 September 2020—24 January 2021
130 days
To those who tried clustering as their solution.
published 19 Jan 2021, 01:44
edited 1 minute later

What's the best lb score you achieved using only clustering and coordinates of crashes? Mine is 44.29.

Note that i don't even use the time component in my current solution meaning that the locations for the ambulances is static time-wise across the submission file.

Hello @blenz

What clustering algorithm did you use ?

I tried Kmeans too but I am getting 105.81

Thinking of ways to improve the score

A default model using kmeans on the crash coordinates with 6 clusters gives around 52.xx. Make sure you're not making a mistake in the creation of the submission file or something

I will do that. Thank you

I have been using the offline scoring function to score my model. I just submitted my submission file to Zindi, and I got 49.xx

yes. with a little tweaking, you should get a lower score.

Hi Blenz, i got 40.42. I modified kmeans by using the geometric median instead means. Kmeans minimizes the squared distances, but the score function is without squares. In fact, it is a well known optimization problem, called the "Multi Source Weber Problem" (MWP).

Thanks for your answer. I've read a little about MWP.

@Marvin27, what library are you using to create your models ?

Hi Bilaerl, because i am a total beginner with python, i started with a pure java program.