Package: themis 1.0.2.9000

Emil Hvitfeldt

themis:Extra Recipes Steps for Dealing with Unbalanced Data

A dataset with an uneven number of cases in each class is said to be unbalanced. Many models produce a subpar performance on unbalanced datasets. A dataset can be balanced by increasing the number of minority cases using SMOTE 2011 <arxiv:1106.1813>, BorderlineSMOTE 2005 <doi:10.1007/11538059_91> and ADASYN 2008 <https://ieeexplore.ieee.org/document/4633969>. Or by decreasing the number of majority cases using NearMiss 2003 <https://www.site.uottawa.ca/~nat/Workshop2003/jzhang.pdf> or Tomek link removal 1976 <https://ieeexplore.ieee.org/document/4309452>.

Authors:Emil Hvitfeldt [aut, cre], Posit Software, PBC [cph, fnd]

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NEWS

# Installthemis in R:
install.packages('themis',repos = c('https://tidymodels.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/tidymodels/themis/issues

Datasets:

On CRAN:

18 exports 140 stars 4.97 score 56 dependencies 1 dependents 5.7k downloads

Last updated 5 months agofrom:0105665987

Exports:adasynbsmotenearmissrequired_pkgssmotesmotencstep_adasynstep_bsmotestep_downsamplestep_nearmissstep_rosestep_smotestep_smotencstep_tomekstep_upsampletidytomektunable

Dependencies:classcliclockcodetoolscpp11data.tablediagramdigestdplyrfansifuturefuture.applygenericsglobalsgluegowerhardhatipredKernSmoothlatticelavalifecyclelistenvlubridatemagrittrMASSMatrixnnetnumDerivparallellypillarpkgconfigprodlimprogressrpurrrR6RANNRcpprecipesrlangROSErpartshapeSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrswithr

Readme and manuals

Help Manual

Help pageTopics
Adaptive Synthetic Algorithmadasyn
borderline-SMOTE Algorithmbsmote
Synthetic Dataset With a Circlecircle_example
Remove Points Near Other Classesnearmiss
SMOTE Algorithmsmote
SMOTENC Algorithmsmotenc
Apply Adaptive Synthetic Algorithmstep_adasyn tidy.step_adasyn
Apply borderline-SMOTE Algorithmstep_bsmote tidy.step_bsmote
Down-Sample a Data Set Based on a Factor Variablestep_downsample tidy.step_downsample
Remove Points Near Other Classesstep_nearmiss tidy.step_nearmiss
Apply ROSE Algorithmstep_rose tidy.step_rose
Apply SMOTE Algorithmstep_smote tidy.step_smote
Apply SMOTENC algorithmstep_smotenc tidy.step_smotenc
Remove Tomek’s Linksstep_tomek tidy.step_tomek
Up-Sample a Data Set Based on a Factor Variablestep_upsample tidy.step_upsample
Remove Tomek's linkstomek