Dec 19, 2023 · These two values share a sigmoidal relationship. However, the specific transformation is dependent on the sample size. Many Dip-based clustering ...

Apr 12, 2023 · This accelerates computation and provides an approximation of the Dip- to Dip-p-value transformation for every single sample size. Further, it ...

Dec 19, 2023 · In the following we explain TailoredDip, which adds two extensions to the UniDip [7] algorithm. First, we show how a cluster can be expanded ...

Feb 7, 2024 · A weighted multivariate signed-rank test is introduced for an analysis of multivariate clustered data. Observations in different clusters may ...

Jan 18, 2023 · This item provides all supplementary material for the paper 'Extension of the Dip-test Repertoire - Efficient and Differentiable p-value ...

Extension of the Dip-test Repertoire-Efficient and Differentiable p-value Calculation for Clustering ... Benchmarking Deep Clustering Algorithms With ClustPy. C ...

An alternative criterion for deciding on the homogeneity of a set of data vectors that is called projected dip, based on the application of unimodality ...

This accelerates computation and provides an approximation of the Dip- to Dip-p-value transformation for every single sample size. Clustering.

The package provides a simple way to perform clustering in Python. For this purpose it provides a variety of algorithms from different domains.

We present experimental results in order to assess the ability of the method to decide on unimodality and perform comparisons with the well-known dip-test ...