Showing 6 of total 6 results (show query)
mhahsler
arules:Mining Association Rules and Frequent Itemsets
Provides the infrastructure for representing, manipulating and analyzing transaction data and patterns (frequent itemsets and association rules). Also provides C implementations of the association mining algorithms Apriori and Eclat. Hahsler, Gruen and Hornik (2005) <doi:10.18637/jss.v014.i15>.
Maintained by Michael Hahsler. Last updated 2 months ago.
arulesassociation-rulesfrequent-itemsets
194 stars 13.99 score 3.3k scripts 28 dependentsquanteda
quanteda.textmodels:Scaling Models and Classifiers for Textual Data
Scaling models and classifiers for sparse matrix objects representing textual data in the form of a document-feature matrix. Includes original implementations of 'Laver', 'Benoit', and Garry's (2003) <doi:10.1017/S0003055403000698>, 'Wordscores' model, the Perry and 'Benoit' (2017) <doi:10.48550/arXiv.1710.08963> class affinity scaling model, and the 'Slapin' and 'Proksch' (2008) <doi:10.1111/j.1540-5907.2008.00338.x> 'wordfish' model, as well as methods for correspondence analysis, latent semantic analysis, and fast Naive Bayes and linear 'SVMs' specially designed for sparse textual data.
Maintained by Kenneth Benoit. Last updated 2 months ago.
42 stars 9.56 score 432 scriptsdivdyn
divDyn:Diversity Dynamics using Fossil Sampling Data
Functions to describe sampling and diversity dynamics of fossil occurrence datasets (e.g. from the Paleobiology Database). The package includes methods to calculate range- and occurrence-based metrics of taxonomic richness, extinction and origination rates, along with traditional sampling measures. A powerful subsampling tool is also included that implements frequently used sampling standardization methods in a multiple bin-framework. The plotting of time series and the occurrence data can be simplified by the functions incorporated in the package, as well as other calculations, such as environmental affinities and extinction selectivity testing. Details can be found in: Kocsis, A.T.; Reddin, C.J.; Alroy, J. and Kiessling, W. (2019) <doi:10.1101/423780>.
Maintained by Adam T. Kocsis. Last updated 4 months ago.
diversityextinctionfossil-dataoccurrencesoriginationpaleobiologycpp
11 stars 6.48 score 137 scriptskpmainali
CooccurrenceAffinity:Affinity in Co-Occurrence Data
Computes a novel metric of affinity between two entities based on their co-occurrence (using binary presence/absence data). The metric and its MLE, alpha hat, were advanced in Mainali, Slud, et al, 2021 <doi:10.1126/sciadv.abj9204>. Various types of confidence intervals and median interval were developed in Mainali and Slud, 2022 <doi:10.1101/2022.11.01.514801>.
Maintained by Kumar Mainali. Last updated 2 years ago.
26 stars 4.39 score 19 scriptsjgill22
hot.deck:Multiple Hot Deck Imputation
Performs multiple hot-deck imputation of categorical and continuous variables in a data frame.
Maintained by Jeff Gill. Last updated 4 years ago.
2.80 score 21 scripts 1 dependents