This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, Hadoop, decision trees, ensembles, correlation, ouliers, regression Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, time series, cross-validation, model fitting, and many more. To keep receiving these articles, sign up on DSC.
15 Articles and Tutorials about Outliers
- Extreme Events Modeling Using Continued Fractions
- Distribution of Arrival Times for Extreme Events
- Robust Regressions: Dealing with Outliers
- Outlier detection with time-series data mining
- Multivariate Outlier Detection
- Sometimes outliers are real data
- Outlier Detection with Parametric and Non-Parametric methods
- Introduction to Outlier Detection Methods
- Neutralizing Outliers in Any Dimension
- Identify, describe, plot, and remove the outliers with R
- Outlier detection using cluster analysis
- Multidimensional outlier detection in time series
- Bayesian Outlier Detection with Dirichlet Process Mixtures
- Book: Outlier Detection for Temporal Data
- Outlier analysis: Chebyschev criteria vs Mutual Information
Forum Questions
- Question: outlier detection and supervised machine learning
- Question: Outliers in Logistic Regression
- Question: Can regression be used for outlier detection
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