02_​Outlier_​Detection_​Solution

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Outlier Detection - exercise

Introduction to Machine Learning Algorithms course - Session 4
Exercise 3
Detect and remove outliers in the data using the following techniques:
- Numeric outliers outside the upper/lower whiskers of a box plot
- Outliers in the distribution tails (z-score)
- Outliers remote from cluster centers (DBSCAN)

URL: Ames Housing Dataset on kaggle https://www.kaggle.com/prevek18/ames-housing-dataset
URL: Description of the Ames Iowa Housing Data https://rdrr.io/cran/AmesHousing/man/ames_raw.html
URL: Four Techniques for Outlier Detection https://www.knime.com/blog/four-techniques-for-outlier-detection
URL: Slides (Introduction to ML Algorithms course) https://www.knime.com/form/material-download-registration

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