A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)

ELKI Data Mining Toolkit

Anomaly detection using LoOP: Local Outlier Probabilities, a local density based outlier detection method providing an outlier score in the range of [0,1].

🌲 Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams

Open-source framework to detect outliers in Elasticsearch events

2D Outlier Analysis using Shiny

RADseq Data Exploration, Manipulation and Visualization using R

Utility library for detecting and removing outliers from normally distributed datasets using the Smirnov-Grubbs test.

Beyond Outlier Detection: LookOut for Pictorial Explanation

Mean Absolute Error Does Not Treat Examples Equally and Gradient Magnitude’s Variance Matters

Genie: A fast and robust hierarchical clustering algorithm (now superseded by genieclust)

Imputation of Financial Time Series with Missing Values and/or Outliers

Image Mosaicing or Panorama Creation

A MATLAB function for robust non-linear least squares

Mean and Covariance Matrix Estimation under Heavy Tails

An algorithm based on Java implementation, can automatically check the set of outliers in a set of data, eliminate these outliers, and finally get normal data.基于java实现的能够自动检查出一组数据中的异常值的集合，剔除这些异常集，得到正常数据。

Visualisation and Outliers Removal via Weka

Package implements a number local outlier factor algorithms for outlier detection and finding anomalous data

Dixon's Q Test calculator package for Dart

Deep Learning for Anomaly Deteection

A beginners tutorial for using Python for exploratory analyses

Anomaly detection algorithms implementations

Single Cell Outlier Selector - quickly find outliers in your single-cell data

Verified the robustness to outliers of Huber Loss with Hinge loss for classification over different datasets.

python package for handling nan's and outliers

Scripts que simulan la aplicación Outliers de IDEA Labs - Caseware IDEA.

Predicting disease spread, a DrivenData competition. I'am currently participating in this competition. I used it as submission for the second capstone project in the course 'Professional Certificate in Data Science' provided by Harvard University (HarvardX) on EDX.

Applied analysis on the Bayesian student-t "Robust" regression model with Jeffrey's prior. Compared its model performance and robustness of posterior distributions with the Gaussian model when outliers are present.