Thank you for your explanation. I also think at 8:15 the multivariate normal distribution's probability density function should have $\sqrt{|\Sigma|}$ in the denominator (rather than $|\Sigma|$ as you have currently) and it also may be helpful to viewers to let them know that $p$ represents the dimension of the space we are considering
10:48 ohhhhh, I was just going back and forth between the sections on LDA and QDA in three different textbooks (An Introduction to Statistical Learning, Applied Predictive Analytics, and Elements of Statistical Learning) for well over an hour and that multivariate normal pdf was really throwing me off big time. Mostly because of the capital sigma to the negative 1st power term, I didn't realize it was literally a capital sigma, I kept thinking it was a summation of something!
Hi! If the classes are assumed to be normally distributed, does that subsume that the features making up an observations are normally distributed as well?
Thanks for this! I needed to clarify these methods in particular, was reading about them in ISLR
A very good and concise explanation, even starting with the explanation of likelihood. Very well done!
Interesting and clear explanation! Thank you very much, this will help me in writing my thesis!
How did your thesis go?
i was trying to read it my self but you made it so much simpler
Thanks! I am glad it was helpful.
This beats my MIT lecture. WIll be coming back for more!
Thank you for your explanation. I also think at 8:15 the multivariate normal distribution's probability density function should have $\sqrt{|\Sigma|}$ in the denominator (rather than $|\Sigma|$ as you have currently) and it also may be helpful to viewers to let them know that $p$ represents the dimension of the space we are considering
I enjoyed watching your video, thank you. I will watch more of your videos on machine learning videos thank you!
Good job. It is very easy to follow and understand
Awesome lecture, thank you professor!
10:48 ohhhhh, I was just going back and forth between the sections on LDA and QDA in three different textbooks (An Introduction to Statistical Learning, Applied Predictive Analytics, and Elements of Statistical Learning) for well over an hour and that multivariate normal pdf was really throwing me off big time. Mostly because of the capital sigma to the negative 1st power term, I didn't realize it was literally a capital sigma, I kept thinking it was a summation of something!
Thankyou so much ! Cleared a lot of my doubts
Very great video! Thank you professor!! :)
Very useful information, thanks you professor!
I am glad its helpful! Thanks for the kind words.
You are so great. Keep up please.
948 Benny Glen
Thank you sir, well explained.
Thanks!
can you share these slides in the videos with me?
very good video, thank you professor
I am glad it is helpful. Thank you for the kind words!
Hi! If the classes are assumed to be normally distributed, does that subsume that the features making up an observations are normally distributed as well?
Yes. If the each class has a multivariate normal distribution than each individual feature variable ihas a single variable normal distribution.
How do you get the values of 0.15 and 0.02? I'm getting different values.
Agreed. I got approximately 0.18 and 0.003, respectively.
could you share the slide？
Young Carol Harris Ruth Clark Jessica