Spread the loveOutliers are data points that significantly differ from the rest of the data, and detecting them is crucial in many fields such as finance, sociology, and medicine. In this article, ...

Calculate useful summary statistics such as median, mean, and standard deviation. These values will provide context for identifying potential outliers by indicating the central tendencies and ...

This video shows hot to find outliers in data by using AutoEncoders. This approach relies on reconstruction errors calculated by AutoEncoders which can be trained in your Jupyter Notebook with Python ...

Article citations More>> Zhao, Y., Nasrullah, Z. and Li, Z. (2019) PyOD: A Python Toolbox for Scalable Outlier Detection. Journal of Machine Learning Research, 20, 1-7. has been cited by the following ...

The Data Science Lab Data Prep for Machine Learning: Outliers After previously detailing how to examine data files and how to identify and deal with missing data, Dr. James McCaffrey of Microsoft ...

Examples of outlier data include a person's age of 99 (either a very old applicant or possibly a placeholder value that was never changed) and a person's country of "Cannada" (probably a transcription ...