Outlier detection with Local Outlier Factor (LOF) | Outlier Detection| Machine Learning Algorithms

Local outlier factor (LOF) is an algorithm used for Unsupervised outlier detection.
It produces an anomaly score that represents data points which are outliers in the data set.
It does this by measuring the local density deviation of a given data point with respect to the data points near it.
Code:
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github.com/Sat...
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[@weidong12369]

Clearly explained. Ty so much!

[@KnowledgeAmplifier1]

You are welcome wd! Happy Learning :-)

[@omarzahran4179]

Thanks, Great explanation.

[@KnowledgeAmplifier1]

You are welcome Omar Zahran! Happy Learning :-)

[@karishmachoudhary5217]

Good job 💯👍

[@Omhange]

full abhyas

[@RaviSharma-ge3cr]

Please upgrade you mic quality or add captions it's quite challenging to focus and think

[@KnowledgeAmplifier1]

Thank you for your feedback Ravi Sharma! Will try to improve in future videos ... Wish you a very Happy New Year ! Stay Tuned

[@gudepuvenkateswarlu5648]

I really appreciate your efforts in making the concepts very clear and interesting to learn. I have small question that "what do we mean by density here?" . Is it simply k-nearest neighbour or anything else? Kindly please clarify. Thanks in advance!

[@ahsanhaider6549]

Please improve mic quality