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ELKI is a free tool for analyzing data, mainly focusing on finding patterns and unusual data points without needing labels. It's written in Java and aims to be fast and able to handle big datasets by using special structures.
In data analysis, anomaly detection (also referred to as outlier detection and sometimes as novelty detection) is generally understood to be the identification of rare items, events or observations which deviate significantly from the majority of the data and do not conform to a well defined notion of normal behavior. [1]
Frequent pattern mining. Itemsets [11] Graphs [12] Change detection algorithms [13] These algorithms are designed for large scale machine learning, dealing with concept drift, and big data streams in real time. MOA supports bi-directional interaction with Weka. MOA is free software released under the GNU GPL.
MOA (Massive Online Analysis): free open-source software specific for mining data streams with concept drift developed in Java. It has several machine learning algorithms (classification, regression, clustering, outlier detection and recommender systems).
Several methods for data cleaning have been implemented including multiple imputations with multivariate imputation by chained equations (MICE) and other techniques, SMOTE, an oversampling technique for class imbalance, forward and backward NA filling, cleaning using schema and length information, support for outlier detection using standard ...
Data mining is a particular data analysis technique that focuses on ... Quantitative data methods for outlier detection, ... Notable free software for data analysis ...
It is a density-based clustering non-parametric algorithm: given a set of points in some space, it groups together points that are closely packed (points with many nearby neighbors), and marks as outliers points that lie alone in low-density regions (those whose nearest neighbors are too far away). DBSCAN is one of the most commonly used and ...
Random sample consensus (RANSAC) is an iterative method to estimate parameters of a mathematical model from a set of observed data that contains outliers, when outliers are to be accorded no influence [clarify] on the values of the estimates. Therefore, it also can be interpreted as an outlier detection method. [1]