Anomaly detection with Isolation Forests

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All of us know random forests, one of the most popular ML models. They are a supervised learning algorithm, used in a wide variety of applications for classification and regression.
Can we use random forests in an unsupervised setting? (where we have no labeled data?)
Isolation forests are a variation of random forests that can be used in an unsupervised setting for anomaly detection.

[@vikashdas1852]

Most probably the best explanation on internet related to Isolation Forest/Anomaly detection

[@brendensong8000]

Excellent Video with a short, clear explanation of the iForest algorithm! thank you for sharing!

[@nicoco5483]

Prolly the clearest explanation I've watched. Much appreciated!

[@insightIQ2023]

True , it is explained very nicely

[@gabrielacuna8530]

Best short explanation I've found on TH-cam. Very straight to the point (pun intended) with clear explanation.

[@chanmad]

anomaly detected

[@mehdioueslati8713]

Extremely clear, thank you!

[@freydunthanos3155]

Got my subscription and bell - thank you so much for the in-depth yet totally understandable explanation!

[@jeromeeusebius]

Thank you for making this video and it's very succint and straight to the point

[@jjbandit3355]

Thank you, this was fantastic!

[@aakashdwivedi5096]

This was great. Thank you very much

[@animeshshukla3534]

Ma'am it was very well explained with all the mathematical details.

[@Moonlight-uv7jo]

Thank you! Very nice explanation:)

[@Bleustar334]

Wow, this video was incredibly informative!

[@avunurishivakumar7972]

Thank you🤗

[@pennyzhang9139]

Thanks. Very clear.

[@tranquochung1995]

Thank you very much

[@hsoley]

amazing, thank you from NYC

[@rabbymustafa3792]

This is a great tutorial

[@vcj3849]

Great work

[@anirbansen4059]

Short and crisp.

[@sheilaabukayo156]

Well explained..

[@InoHimeYa]

Very understandable

[@machinelearning4611]

[@Piyush4113]

Please can anybody explain what is the difference between E(h(x)) and c(m) because E(h(x)) is also the average values of h(x) over all iTrees and c(m) is also the average value of h(x)? Please i am really confused what is the difference between them!!

[@emamulmursalin9181]

E(h(x)) is the average values of h(x) over all iTrees but only for data point "x"
c(m) is the same but it is calculated only from the "m" samples from the training dataset

[@mohammedsufyan6950]

mam what type of feature we are selecting here

[@andrea-mj9ce]

What's an isolation tree then ?

[@trrao835]

great explanation. Thanks