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densratio - Density Ratio Estimation

Density ratio estimation. The estimated density ratio function can be used in many applications such as anomaly detection, change-point detection, covariate shift adaptation. The implemented methods are uLSIF (Hido et al. (2011) <doi:10.1007/s10115-010-0283-2>), RuLSIF (Yamada et al. (2011) <doi:10.1162/NECO_a_00442>), and KLIEP (Sugiyama et al. (2007) <doi:10.1007/s10463-008-0197-x>).

Last updated

anomaly-detectionmachine-learningstatistics

6.91 score 23 stars 3 dependents 79 scripts 708 downloads

magicfor - Magic Functions to Obtain Results from for Loops

Magic functions to obtain results from for loops.

Last updated

r-language

5.79 score 20 stars 61 scripts 531 downloads

TheseusPlot - Visualizing Decomposition of Differences in Rate Metrics

Provides tools for decomposing differences in rate metrics between two groups into contributions from individual subgroups and visualizing them as a "Theseus Plot". Inspired by the story of the Ship of Theseus, the method replaces subgroup data from one group with that of another step by step, recalculating the overall metric at each stage to quantify subgroup contributions. A Theseus Plot combines the stepwise progression of a waterfall plot with the comparative bars of a bar chart, offering an intuitive way to understand subgroup-level effects.

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data-sciencedata-visualization

4.60 score 5 stars 9 scripts 518 downloads

deltatest - Statistical Hypothesis Testing Using the Delta Method

Statistical hypothesis testing using the Delta method as proposed by Deng et al. (2018) <doi:10.1145/3219819.3219919>. This method replaces the standard variance estimation formula in the Z-test with an approximate formula derived via the Delta method, which can account for within-user correlation.

Last updated

ab-testingdata-sciencestatistics

4.35 score 7 stars 16 scripts 199 downloads

sGMRFmix - Sparse Gaussian Markov Random Field Mixtures for Anomaly Detection

An implementation of sparse Gaussian Markov random field mixtures presented by Ide et al. (2016) <doi:10.1109/ICDM.2016.0119>. It provides a novel anomaly detection method for multivariate noisy sensor data. It can automatically handle multiple operational modes. And it can also compute variable-wise anomaly scores.

Last updated

2.34 score 1 stars 22 scripts 241 downloads