Hi, I wanted to ask you a question. I understood your reasoning by comparing circles and indicating as an outlier if the point of my observation is larger than that of its neighbors. But in reality it is wrong to say that it is an outlier because it has a higher density than the density of its neighbors. High density means he has samples very close to him, low density means he has samples very far from him. Therefore, the sample that is very far from the other samples, and therefore has a lower density, is an outlier. Tell me if you understand what I mean, if you can correct me you'll do me a favor.
No problem at all! In reality the circles represent the opposite of density and more reachability. So the larger the circles mean the larger the reachability (inverse of density). That is what makes the large circles more likely to be outliers! Hope this helps!
@@AricLaBarr This was confusing me as well because in the video, you were referring to the circular area as the density of the point instead of the reachability.
At 1:50 the density is defined as the inverse of the average reachability ... Somehow the 'inverse' was ignored after that which flips the meaning of density after that point.
That is straight to the point. Better than all the blogs I have gone through to understand LOF
Somehow you make these videos extremely informative in only 5 minutes. What a legend.
Amazing way of explaining
salute to this dude for the clarity of his explanations
This series is truly unique; please keep it going.
I was super lost thanks for explaining it amazingly!
super useful to understand complex subject. hope to see the rest of machine learning approaches video soon
Thanks! I plan on making more videos, but can't promise when!
Please continue the series sir
Hi, I wanted to ask you a question. I understood your reasoning by comparing circles and indicating as an outlier if the point of my observation is larger than that of its neighbors. But in reality it is wrong to say that it is an outlier because it has a higher density than the density of its neighbors. High density means he has samples very close to him, low density means he has samples very far from him. Therefore, the sample that is very far from the other samples, and therefore has a lower density, is an outlier.
Tell me if you understand what I mean, if you can correct me you'll do me a favor.
No problem at all! In reality the circles represent the opposite of density and more reachability. So the larger the circles mean the larger the reachability (inverse of density). That is what makes the large circles more likely to be outliers!
Hope this helps!
@@AricLaBarr Okey, Thanks again.
@@AricLaBarr This was confusing me as well because in the video, you were referring to the circular area as the density of the point instead of the reachability.
Very well explained thank you
Tellement bien expliquée! merci
At 1:50 the density is defined as the inverse of the average reachability ... Somehow the 'inverse' was ignored after that which flips the meaning of density after that point.
Thanks!
thanks good video
Nice.
That is straight to the point. Better than all the blogs I have gone through to understand LOF