This explanation is missing in most of the presentations, I've seen. It would be a value addition, if you can add explanation on the calculation of the no. of computations without the simplification and with simplification. thank you
No, the image which is wrongly classified is given higher importance (due to an error) than the image which was correctly classified (no error). But in case of feature, the feature which gives less error it means it is a better classifier therefore it's weight ( or importance) is higher. That's what I understood.
super clear thank you
Ty so much for share this!
Very helpful video!
Thank you
Very Helpful Video👌
Thank you for sharing 😏
This explanation is missing in most of the presentations, I've seen. It would be a value addition, if you can add explanation on the calculation of the no. of computations without the simplification and with simplification.
thank you
Today's best face detection algorithm?????
Can you please share the ppt
can you share the link of ppt you used in the video?
he saying the feature with low error is given a higher importance ? is should not be the feature with higher error?
Hello! Please if you got the answer to this question, I'll be thankful for an explanation
No, the image which is wrongly classified is given higher importance (due to an error) than the image which was correctly classified (no error). But in case of feature, the feature which gives less error it means it is a better classifier therefore it's weight ( or importance) is higher.
That's what I understood.
just a suggestion, when you breath in, move your mouth away from mic.