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Outliers are data points that significantly differ from the rest of the dataset. For example, if we collect data from a high school and find a 90-year-old, that age is considered an outlier, as all students should be teenagers.

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What are Outliers? Outliers are those data points that significantly deviate from the rest of the data. What are the types of outliers? There are three major types of outliers: 1. Global Outliers, 2. Contextual Outliers, 3. Collective Outliers How do we identify outliers? We can identify outliers in various ways, such as Plotting (Box Plot, Histogram, Scatter Plot), IQR, and Z-score method. How do we deal with outliers? We can deal with them in various ways, such as removing them, transformation, imputation, and Using Robust Models.

What are outliers? What are types of outliers? How can identifiy outliers? Steps to remove outliers by using Inter quartile range methods? Steps to remove outliers by using zscore methods? How to deal with outliers?

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Outliers are disturbing the performance of ml model With outliers we can able to take decision on the data

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Outliers are the anomalies in the dataset that disturb the machine learning and give biased results.