What is Outlier?
June 15, 2023
What is Outlier?
“Outlier is an observation in a dataset situated at an abnormal distance from other values in the exact same dataset.” In data mining, outliers are considered significant because they can remarkably impact the analysis and modeling of data. Therefore, it is essential to identify and handle outliers appropriately to ensure accurate results.
Essentially, an outlier is a data point that is remarkably distinct from other data points in a dataset.
TYPES OF OUTLIERS IN DATA MINING
1. Univariate Outliers :
Univariate outliers are observations that lie significantly outside the range of the majority of the data points in a single variable dataset. This means they have an unusually high or low value compared to the remainder of the data in that single variable.
2. Contextual Outliers :
Contextual outliers refer to data points that deviate significantly from the norm in the context of a specific dataset. These outliers are different from univariate outliers, which are based on a single variable and may be outliers in that single dimension but are not necessarily outliers in the context of the dataset as a whole.
3. Collective Outliers :
Collective outliers refer to a group of observations that deviate significantly from the norm within a dataset. Unlike individual outliers, which are isolated observations that differ from the remaining data, collective outliers represent a pattern of unusual observations occurring together.
Interview Questions :
1. What is Outlier?
2. What are the types of outliers ?
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