Curated list of Outlier Detection Resources

Curated list of Outlier Detection Resources

Last updated on August 1, 2020. I am continuously updating this post. In data mining, anomaly detection (also outlier detection) is the identification of rare items.

In data mining, anomaly detection (also outlier detection) is the identification of rare items, events or observations which raise suspicions by differing significantly from the majority of the data. — [Wikipedia_](https://en.wikipedia.org/wiki/Anomaly_detection)._

This post contents:

  1. Books
  2. Research Papers

Books

Outlier Analysis by Charu C. Aggarwal.

Outlier Ensembles by Charu C. Aggarwal, Saket Sathe.


Research Papers

Survey Papers

Anomaly detection: A survey

Novelty detection: a review — part 1: statistical approaches

Novelty detection: a review — part 2:: neural network based approaches

A Survey of Outlier Detection Methodologies

State-of-the-art Methods

LOF: Identifying Density-Based Local Outliers

Isolation Forest

Density Based Outlier Detection Methods

LOF: Identifying Density-Based Local Outliers

LOCI: fast outlier detection using the local correlation integral

Revisiting Attribute Independence Assumption in Probabilistic Unsupervised Anomaly Detection

OPTICS-OF: Identifying Local Outliers

A local density-based approach for outlier detection

An efficient algorithm for distributed density-based outlier detection on big data

LoOP: Local Outlier Probabilities

Distance Based Outlier Detection Methods

A New Local Distance-Based Outlier Detection Approach for Scattered Real-World Data

Distance-based Outlier Detection in Data Streams

Rapid Distance-Based Outlier Detection via Sampling

Angle-based outlier detection in high-dimensional data

Scalable distance-based outlier detection over high-volume data streams

Fast mining of distance-based outliers in high-dimensional datasets

Distance-Based Outlier Detection on Uncertain Data

Distance-based outlier detection: consolidation and renewed bearing

Clustering Based Outlier Detection Methods

Cluster-based outlier detection

Clustering-Based Outlier Detection Method

Efficient Clustering-Based Outlier Detection Algorithm for Dynamic Data Stream

An Outlier Detection Method Based on Clustering

Cluster Based Outlier Detection Algorithm for Healthcare Data

A Minimum Spanning Tree-Inspired Clustering-Based Outlier Detection Technique

Framework of Clustering-Based Outlier Detection

anomaly-detection outlier-detection learning resources machine-learning deep learning

Bootstrap 5 Complete Course with Examples

Bootstrap 5 Tutorial - Bootstrap 5 Crash Course for Beginners

Nest.JS Tutorial for Beginners

Hello Vue 3: A First Look at Vue 3 and the Composition API

Building a simple Applications with Vue 3

Deno Crash Course: Explore Deno and Create a full REST API with Deno

How to Build a Real-time Chat App with Deno and WebSockets

Convert HTML to Markdown Online

HTML entity encoder decoder Online

These Tips Will Help You Step Up Anomaly Detection Using ML

Learn different Machine Learning-Based Approaches for Anomaly Detection and how to apply on the dataset to solve a problem.

Deep Learning for Anomaly Detection: A Comprehensive Survey

Reviewing challenges, methods and opportunities in deep anomaly detection. This post summarizes a comprehensive survey paper on deep learning for anomaly detection .

Credit Card Fraud Detection via Machine Learning: A Case Study

Credit Card Fraud Detection via Machine Learning: A Case Study. A machine learning guide on how to identify fraudulent credit card transactions by using the PyOD toolkit.

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