A hospital in the province of Greenland has been trying to improve its care conditions by looking at historic survival of the patients. They tried looking at their data but could not identify the main factors leading to high survivals.
thanks a lot for sharing the feedback @rubenkerkhofs we shall definitely incorporate this.
Just giving heads up, we just added this as a practice challenge from our previous bootcamp and it is independent of the ongoing Deep Learning Bootcamp. Cheers!
I tried submitting my model’s prediction values in the Solve in this format:
predictions = [0.4436, 0.4554, 0.5…]
but it says wrong answer. Is something missing here?
Sunny
@sunny, it expects to receive the predicted labels (not the score) i.e. ones and zeros. An example is the list [0, 1, 1, 0, 1, 0, 0, …] . You have to define a cut-off value and label everything above the cut-off as 1 and below the cut-off as 0.
I submitted my prediction, but my submission turned out to be wrong.
My prediction contains only 0 and 1, which has 9303 length.
I want to know how to submit.
Yeah, so the evaluation dataset contains 9303 observations like mentioned by @masa2197; however, when I submitted a list of 9303 elements it rejected my submission. When I then tried to submit a list of 23097 observations (the length of the train dataset) it worked.
But tbh, I just wanted to try out the submission platform with this challenge so I did not check very thoroughly what was and was not correct
Hi @rubenkerkhofs@masa2197@abhiram
Thanks for putting it across. We are looking into this issue. Once done we will let you guys know in this tread only. However there was wrong dataset link placed in test data. Our apology for this. We have changed the test dataset link which have 9330 records.