85 citations · 254 across the 14 of their papers we have counts for
7 papers · 1 filter
Minimalist Data Wrangling with Python
Marek Gagolewski
Minimalist Data Wrangling with Python is envisaged as a student's first introduction to data science, providing a high-level overview as well as discussing key concepts in detail.…
Genie: A new, fast, and outlier-resistant hierarchical clustering algorithm
Marek Gagolewski, Maciej Bartoszuk, Anna Cena
The time needed to apply a hierarchical clustering algorithm is most often dominated by the number of computations of a pairwise dissimilarity measure. Such a constraint, for large…
A framework for benchmarking clustering algorithms
Marek Gagolewski
The evaluation of clustering algorithms can involve running them on a variety of benchmark problems, and comparing their outputs to the reference, ground-truth groupings provided b…
Normalised clustering accuracy: An asymmetric external cluster validity measure
Marek Gagolewski
There is no, nor will there ever be, single best clustering algorithm. Nevertheless, we would still like to be able to distinguish between methods that work well on certain task ty…
Data Fusion: Theory, Methods, and Applications
Marek Gagolewski
A proper fusion of complex data is of interest to many researchers in diverse fields, including computational statistics, computational geometry, bioinformatics, machine learning,…
Are Cluster Validity Measures (In)valid?
Marek Gagolewski, Maciej Bartoszuk, Anna Cena
Internal cluster validity measures (such as the Calinski-Harabasz, Dunn, or Davies-Bouldin indices) are frequently used for selecting the appropriate number of partitions a dataset…
Power Laws, the Price Model, and the Pareto type-2 Distribution
Grzegorz Siudem, Przemysław Nowak, Marek Gagolewski
We consider a version of D. Price's model for the growth of a bibliographic network, where in each iteration a constant number of citations is randomly allocated according to a wei…