Dear Jose,

 

I just want to get a clarification about the below pseudo-code. Should it be applied only when dealing with sample of the test dataset or the complete test dataset as well?

 

Regards,

زياد بن أحمد المريشد
أخصائي استخراج بيانات
التحليل الابداعي للبيانات


Ziyad A. Moraished
Data Mining Specialist
Analytics Innovation

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From: Challenge-kdn <challenge-kdn-bounces@mail.knowledgedefinednetworking.org> on behalf of José Suárez-Varela <jsuarezv@ac.upc.edu>
Date: Monday, 28 September 2020 at 9:08 PM
To: "challenge-kdn@mail.knowledgedefinednetworking.org" <challenge-kdn@mail.knowledgedefinednetworking.org>
Subject: [GNNet challenge 2020] Correction in the instructions for the evaluation phase

 

Dear participants,

We found a small error in the document with the instructions for the evaluation phase. Particularly, to generate the output CSV format with your solutions you can use the following pseudo-code:

String = “”
For node_src in range (19):
    For node_dst in range (19):
        If node_src != node_dst:
            String += str(delay[node_src, node_dst])+”;”
# New sample, new line
String +=”\n”

This skips the node pairs where the source and destination match, thus resulting in 342 src-dst delay values (i.e., 19 sources x 18 destinations = 342 values).

Please find attached a new version of the instruction document fixing this error.

Also, to help you validate the format of your submission files, I attach a ZIP file with the expected format when applying a solution to our toy validation dataset (https://github.com/knowledgedefinednetworking/RouteNet-challenge/tree/master/data/sample_data/validation). Note that in this case the results correspond to a 17-node network, so we have 17x16=272 src-dst delay values per line. However, with the final test dataset we should expect 342 values per line.

I would like to take this opportunity to encourage you to register on our evaluation platform in advance to avoid potential problems before the evaluation phase starts (October 1st).

 

 

Best regards,

José Suárez-Varela

Barcelona Neural Networking center

Universitat Politècnica de Catalunya

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