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?

war jata jutt saab

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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.

Phir Program to var giya

- Outliers are unexpected or random values - Outliers leads to causes wrong prediction like missing values - Outliers are anomalies in data - Outliers are mistakes during data collection - Outliers are will cause to wrong insights from data

Outliers are the anomalies of the data that will disturb the whole analysis of the data. 2. So we have to find them and reduce or impute them using different methods. 3. There are also different types of outliers so we have to consider them while detecting them. 4. We can use statistical methods like Inter Quartile Range or Visualization methods to detect outliers and to deal with them we can remove them, transform them, or impute them. 5. So we must deal with these because if not then it will create issues in the future.

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