How do outliers affect the accuracy of machine learning models?

How do outliers affect the accuracy of machine learning models?

Outliers can significantly skew the results of a model, leading to inaccurate predictions. They can affect the mean and variance, which in turn impacts the model's performance.

Can you give an example of how an outlier might change a model's predictions?

Sure! For instance, in a dataset predicting house prices, if most houses are priced between $200,000 and $500,000, but one house is listed at $2 million, this outlier can pull the average price up, misleading the model.

What techniques can be used to handle outliers?

Common techniques include removing outliers, transforming data, or using robust statistical methods that are less sensitive to outliers.

Are there situations where outliers should be kept in the dataset?

Yes, if the outliers represent valid variations in the data or are critical for understanding the problem, they should be retained.