We just talked about this in my machine learning course this week!! Great timing! This video is very helpful.

thank you! love to see those results comparison

Basically there is no way to escape just getting more samples. In my case there is a huge imbalance, but at least false positives are much scarier as a result

Well presented!

ritvikmath coming with a video of one of my favorite topics - instant like!

Great content, these practical content is gold. Thank you :)

Thank you so much for all you do.

Hi! Great video. Is there any way you would like to creat a full in-depth catboost tutorial on some random data? Would be super useful.

Great video. For other ML algorithms like logistic regression, SVM, KNN etc, can we implement the first method (upweight the minority class) ? or this is only applicable to decision tree ?

you are seriously so underrated

very interesting.  AdTech modeling of conversions as caused by advertising always suffers from imbalance.  (Conversion rates are usually low-mid single digits).

Great video!

But don’t you think with such unbalanced dataset it would be better going for an anomaly detection algorithm instead of classification algorithm?

Can we customise loss function? For example more weight for misclassification of true minor class and less weight for the other error?

Okey, but with oversampling - how do you use cross validation ? Because if you use it on the oversampled dataset, you'll have dataleak

Excellent video!

One question though: are certain classification models immune from class imbalance? Thanks!

Great demo!
just one thought, why did you not talk about downsampling the majority class? and see what can be the impact?

It should be "imbalanced data" instead of "unbalanced data"

Hi just wondering if SMOTE is applicable for image data? I saw only one article on it online, so I am not sure if it even works since generating synthetic images is likely much harder.

You could predict that aircraft engines NEVER fail and almost always be right.

Are you familiar with Latent vectors in network analysis?

s/o from South Africa