2.7. Novelty and Outlier Detection2.7. Novelty and Outlier Detection# Many applications require being able to decide whether a new observation belongs to the same distribution as existing observations (it is an inlier), or should be considered as different (it is an outlier). Often, this ability is used to clean real data sets. Two important distinctions must be made: outlier detection: The training data contains outliers which ar
