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Found 8 papers, 1 papers with code
TSLiNGAM: DirectLiNGAM under heavy tails
TSLiNGAM leverages the non-Gaussianity assumption of the error terms in the LiNGAM model to obtain more efficient and robust estimation of the causal structure.
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.
Weight-of-evidence 2.0 with shrinkage and spline-binning
We present the results of a series of experiments in a fraud detection setting, which illustrate the effectiveness of the presented approach.
Regularized K-means through hard-thresholding
We study a framework of regularized $K$-means methods based on direct penalization of the size of the cluster centers.
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).
