Package: catlearn 1.1

catlearn: Formal Psychological Models of Categorization and Learning

Formal psychological models of categorization and learning, independently-replicated data sets against which to test them, and simulation archives.

Authors:Andy Wills [aut, cre], Lenard Dome [aut], Charlotte Edmunds [aut], Garrett Honke [aut], Angus Inkster [aut], René Schlegelmilch [aut], Stuart Spicer [aut]

catlearn_1.1.tar.gz
catlearn_1.1.zip(r-4.7)catlearn_1.1.zip(r-4.6)catlearn_1.1.zip(r-4.5)
catlearn_1.1.tgz(r-4.6-x86_64)catlearn_1.1.tgz(r-4.6-arm64)catlearn_1.1.tgz(r-4.5-x86_64)catlearn_1.1.tgz(r-4.5-arm64)
catlearn_1.1.tar.gz(r-4.7-arm64)catlearn_1.1.tar.gz(r-4.7-x86_64)catlearn_1.1.tar.gz(r-4.6-arm64)catlearn_1.1.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html✨
card.svg |card.png
catlearn/json (API)

# Install 'catlearn' in R:

install.packages('catlearn', repos = c('https://ajwills72.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/ajwills72/catlearn/issues

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3

Datasets:

homa76 - Category breadth CIRP
krus96 - Inverse Base-rate Effect AP
nosof88 - Instantiation frequency CIRP
nosof94 - Type I-VI category structure CIRP
shin92 - Category size CIRP
thegrid - Ordinal adequacy results for all catlearn simulations

On CRAN:

categorization cognitive-science formal-models learning learning-theory open-models open-science psychology openblas cpp

5.47 score 29 stars 51 scripts 703 downloads 39 exports 26 dependencies

Last updated from:cc8b192cf1. Checks:12 OK, 1 FAIL. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	220
linux-devel-x86_64	OK	168
source / vignettes	OK	230
linux-release-arm64	OK	221
linux-release-x86_64	OK	164
macos-release-arm64	OK	158
macos-release-x86_64	OK	400
macos-oldrel-arm64	OK	158
macos-oldrel-x86_64	OK	392
windows-devel	OK	175
windows-release	OK	161
windows-oldrel	OK	150
wasm-release	FAIL	115

Exports:act2probrat convertSUSTAIN krus96exit krus96train medin87train nosof88exalcove nosof88exalcove_opt nosof88oat nosof88protoalcove nosof88protoalcove_opt nosof88train nosof94bnalcove nosof94exalcove nosof94exalcove_opt nosof94oat nosof94plot nosof94sustain nosof94train shin92exalcove shin92exalcove_opt shin92oat shin92protoalcove shin92protoalcove_opt shin92train slpALCOVE slpBM slpCOVIS slpDGCM slpDIVA slpEXIT slpLMSnet slpMack75 slpMBMF slpNNCAG slpNNRAS slpRW slpSUSTAIN ssecl stsimGCM

Dependencies:cli codetools cpp11 doParallel dplyr foreach generics glue iterators lifecycle magrittr pillar pkgconfig purrr R6 Rcpp RcppArmadillo rlang stringi stringr tibble tidyr tidyselect utf8 vctrs withr

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Formal Modeling for Psychology.	catlearn-package
Convert output activation to a rating of outcome probability	act2probrat
Convert nominal-dimension input representation into a 'padded' (slpSUSTAIN) format	convertSUSTAIN
Category breadth CIRP	homa76
Inverse Base-rate Effect AP	krus96
Simulation of AP krus96 with EXIT model	krus96exit
Input representation of krus96 for models input-compatible with slpEXIT	krus96train
Input representation of Exp. 1 in Medin et al. (1987) for models input-compatible with slpALCOVE or slpSUSTAIN.	medin87train
Instantiation frequency CIRP	nosof88
Simulation of CIRP nosof88 with ex-ALCOVE model	nosof88exalcove
Parameter optimization of ex-ALCOVE model with nosof88 CIRP	nosof88exalcove_opt
Ordinal adequacy test for simulations of nosof88 CIRP	nosof88oat
Simulation of CIRP nosof88 with proto-ALCOVE model	nosof88protoalcove
Parameter optimization of proto-ALCOVE model with nosof88 CIRP	nosof88protoalcove_opt
Input representation of nosof88 for models input-compatible with slpALCOVE.	nosof88train
Type I-VI category structure CIRP	nosof94
Simulation of CIRP nosof94 with BN-ALCOVE model	nosof94bnalcove
Simulation of CIRP nosof94 with ex-ALCOVE model	nosof94exalcove
Parameter optimization of ex-ALCOVE model with nosof94 CIRP	nosof94exalcove_opt
Ordinal adequacy test for simulations of nosof94 CIRP	nosof94oat
Plot Nosofsky et al. (1994) data / simulations	nosof94plot
Simulation of CIRP nosof94 with the SUSTAIN model	nosof94sustain
Input representation of nosof94 for models input-compatible with slpALCOVE or slpSUSTAIN	nosof94train
Category size CIRP	shin92
Simulation of CIRP shin92 with ex-ALCOVE model	shin92exalcove
Parameter optimization of ex-ALCOVE model with shin92 CIRP	shin92exalcove_opt
Ordinal adequacy test for simulations of shin92 CIRP	shin92oat
Simulation of CIRP shin92 with proto-ALCOVE model	shin92protoalcove
Parameter optimization of proto-ALCOVE model with shin92 CIRP	shin92protoalcove_opt
Input representation of shin92 for models input-compatible with slpALCOVE.	shin92train
ALCOVE category learning model	slpALCOVE
Bush & Mosteller (1951) simple associative learning model	slpBM
COVIS category learning model	slpCOVIS
Similarity-Dissimilarity Generalized Context Model (DGCM)	slpDGCM
DIVA category learning model	slpDIVA
EXIT Category Learning Model	slpEXIT
Gluck & Bower (1988) network model	slpLMSnet
Mackintosh (1975) associative learning model	slpMack75
MB/MF reinforcement learning model	slpMBMF
A Neural Network with Competitive Attentional Gating (NNCAG)	slpNNCAG
A Neural Network with Rapid Attentional Shifts (NNRAS)	slpNNRAS
Rescorla-Wagner (1972) associative learning model.	slpRW
SUSTAIN Category Learning Model	slpSUSTAIN
Sum of squared errors	ssecl
Generalized Context Model	stsimGCM
Ordinal adequacy results for all catlearn simulations	thegrid