Bootstrapping refers to the process of sampling data with replacement
Adapted from Bayes’ Rule, the basic setup of Bayesian inference is
Classical Statistics is based around the notion that population parameters of a model are unknown but fixed
As Mahalanobis Distance measures the distance of each observation to the distribution of surrounding data points in higher dimensional space
This algorithm uses an approach like K-nearest neighbors (KNN) to quantify the dissimilarity of an observation.
Isolation Forest works as an anomaly detection approach and is based on the Random Forest algorithm.
Some automatic outlier detection mechanisms are: Isolation Forest, Local Outlier Factor, and Mahalanobis Distance
As outliers are observed data points, the very first step that should be taken is to understand what resulted in the outlier.
An outlier is an observation that is located far away relative to the distribution of the remaining observations.
Skewness measures the degree of symmetry present in a distribution.