this is a great explanation, I saw some people didn't like this video I think the reason is that they didn't follow the earlier ones. so my advice is to start watiching from the 6th epesode in this playlist. again thanks for the author.
By far this is the clearest explanation of this topic I found on the internet. Great job :) Note that in both examples all relevant documents are retrieved. I'm wondering how a real implementation of this can work. So, what happens if one of the relevant document gets ranked at the end of that corpus of 2 billion documents? Should the rank be computed to all that documents until the last relevant document appears, and then compute the average? Perhaps one can define a sort of maximum number of results to compute, and if not all relevant documents are retrieved, stop the retrieval process, and assigning zero to all non retrieved relevant documents. Is it there any standard way to to this? Any word about this kind of considerations will be appreciated. Thanks!
According to Wikipedia it seems the way to work around that is as I suggested above. en.wikipedia.org/wiki/Information_retrieval Wikipedia says "Note that the average is over all relevant documents and the relevant documents not retrieved get a precision score of zero."
It's really a good explaination on MAP with an example too. Don't know why people disliked it. Probably they dont have prior knowledge related to this . Thanks alot , man.
this is a great explanation, I saw some people didn't like this video I think the reason is that they didn't follow the earlier ones.
so my advice is to start watiching from the 6th epesode in this playlist. again thanks for the author.
Thank you! The lecture starts here: ruclips.net/video/K-eM3eLIEpw/видео.html
thank you very much
Great video! Easiest way to understand anything is always a simple example instead of complicated definitions
Finally someone pragmatic on this one! No long formulas and blablaas. Hands on! great video, thank you Victor 😉
Thanks a lot! Even 7 years later, your video really helped me out!
2:30 Perfect slide. 4 minutes including everything you need to know about MPA. Thank you!
By far this is the clearest explanation of this topic I found on the internet.
Great job :)
Note that in both examples all relevant documents are retrieved.
I'm wondering how a real implementation of this can work. So, what happens if one of the relevant document gets ranked at the end of that corpus of 2 billion documents?
Should the rank be computed to all that documents until the last relevant document appears, and then compute the average?
Perhaps one can define a sort of maximum number of results to compute, and if not all relevant documents are retrieved, stop the retrieval process, and assigning zero to all non retrieved relevant documents. Is it there any standard way to to this?
Any word about this kind of considerations will be appreciated.
Thanks!
According to Wikipedia it seems the way to work around that is as I suggested above.
en.wikipedia.org/wiki/Information_retrieval
Wikipedia says "Note that the average is over all relevant documents and the relevant documents not retrieved get a precision score of zero."
This is brilliant! It's very difficult to find that good resources on this on the internet!
It's really a good explaination on MAP with an example too. Don't know why people disliked it. Probably they dont have prior knowledge related to this . Thanks alot , man.
how we calculated Precision and recall for every document, could you please help me.?
Dear Victor, could you please upload a PPT/PDF so we can read it offline or on the go ? Thank you
It helped me a lot thank you! It gives an illustration of what tells Wikipedia.
Sir..This lecture was really great..it would be very helpful if you kindly explain how to use MAP with K-Fold cross validation. Thanks again.
Awesome! Example helped a lot!
Why mean average precision works?? For me, its just some random computation.
I know hat now, thanks, again
@@yb801 lmao it took you a year to get that
Thanks! great explanation. Save my day!
Saved my assignment 🙌👍
Very nice!
thank you sir
here's the link to the complete playlist: ruclips.net/p/PLBv09BD7ez_6nqE9YU9bQXpjJ5jJ1Kgr9
Thank you! :)
nice explanation sir
Andrew Tate?
Nice video, BTW, thanks
great