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K-Means Cluster Analysis & Outlier Detection by senthilkumar07032024 is a document available to read on EtoBox.

What is K-Means Cluster Analysis & Outlier Detection about?

K-Means clustering was utilized to segment a dataset of 310 points into three clusters after standardization. An Isolation Forest model was employed for outlier detection, identifying 16 potential anomalies. The analysis successfully identified clusters and outliers within the data.

Author

senthilkumar07032024

Language

EN