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Found 10 papers, 3 papers with code
Fast Linear Model Trees by PILOT
Linear model trees are regression trees that incorporate linear models in the leaf nodes.
The Cellwise Minimum Covariance Determinant Estimator
On the other hand, cellwise outliers are individual cells in the data matrix.
Silhouettes and quasi residual plots for neural nets and tree-based classifiers
Here we pursue a different goal, which is to visualize the cases being classified, either in training data or in test data.
Fast and Eager k-Medoids Clustering: O(k) Runtime Improvement of the PAM, CLARA, and CLARANS Algorithms
While we do not study the parallelization of our approach in this work, it can easily be combined with earlier approaches to use PAM and CLARA on big data (some of which use PAM as a subroutine, hence can immediately benefit from these improvements), where the performance with high k becomes increasingly important.
Outlier detection in non-elliptical data by kernel MRCD
The minimum regularized covariance determinant method (MRCD) is a robust estimator for multivariate location and scatter, which detects outliers by fitting a robust covariance matrix to the data.
Class maps for visualizing classification results
A classification method first processes a training set of objects with given classes (labels), with the goal of afterward assigning new objects to one of these classes.
Transforming variables to central normality
Many real data sets contain numerical features (variables) whose distribution is far from normal (gaussian).
Faster k-Medoids Clustering: Improving the PAM, CLARA, and CLARANS Algorithms
It can easily be combined with earlier approaches to use PAM and CLARA on big data (some of which use PAM as a subroutine, hence can immediately benefit from these improvements), where the performance with high k becomes increasingly important.
Robust Monitoring of Time Series with Application to Fraud Detection
Time series often contain outliers and level shifts or structural changes.
Computation
Anomaly Detection by Robust Statistics
Real data often contain anomalous cases, also known as outliers.
