3 methods to deal with outliers

An outlier is a data point that is distant from other similar points. They may be due to variability in the measurement or may indicate experimental errors. If possible, outliers should be excluded from the data set. However, detecting that anomalous instances might be very difficult, and is not always possible. Machine learning algorithms are very sensitive to the range and distribution of attribute values.