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EmilHvitfeldtEmilHvitfeldt
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Merge pull request #171 from tidymodels/RC-0.2.0
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‎.Rbuildignore

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^vignettes/articles$
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^cran-comments\.md$
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^CRAN-SUBMISSION$
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^revdep$

‎.gitignore

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.DS_Store
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docs
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hex sticker/
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revdep/checks.noindex
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revdep/library.noindex
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revdep/data.sqlite
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.httr-oauth
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revdep/cloud.noindex/*

‎DESCRIPTION

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Package: tidyclust
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Title: A Common API to Clustering
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Version: 0.1.2.9000
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Version: 0.2.0.9000
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Authors@R: c(
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person("Emil", "Hvitfeldt", , "[email protected]", role = c("aut", "cre"),
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comment = c(ORCID = "0000-0002-0679-1945")),
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License: MIT + file LICENSE
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URL: https://github.com/tidymodels/tidyclust, https://tidyclust.tidymodels.org/
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BugReports: https://github.com/tidymodels/tidyclust/issues
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Depends:
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R (>= 3.6)
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Imports:
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cli (>= 3.0.0),
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dials (>= 1.1.0),

‎NEWS.md

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# tidyclust (development version)
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# tidyclust 0.2.0
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## New Engines
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* The clustMixType engine as been added to `k_means()`. This engine allows fitting of k-prototype models. (#63)
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* The klaR engine as been added to `k_means()`. This engine allows fitting of k-modes models. (#63)
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## Improvements
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* Engine specific documentation has been added for all models and engines. (#159)
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## Bug Fixes
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* Fixed bug where engine specific arguments were passed along for `k_means()` when the engine ClusterR. (#142)
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* Fixed bug where `prefix` argument wouldn't be correctly passed through `extract_cluster_assignment()`, `extract_centroids()`, and `predict()` (#145)
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* `k_means()` now errors informatively if `fit()` without `num_clust` specified. (#134)
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* Exported internal functions `ClusterR_kmeans_fit()`, `stats_kmeans_fit()`, and `hclust_fit()` have been renamed to `.k_means_fit_ClusterR()`, `.k_means_fit_stats()`, and `.hier_clust_fit_stats()` to reduce visibility for users.
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* The clustMixType engine as been added to `k_means()`. This engine allows fitting of k-prototype models. (#63)
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* Fixed bug where levels didn't match number of clusters if prediction on fewer number of observations. (#158)
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* The klaR engine as been added to `k_means()`. This engine allows fitting of k-modes models. (#63)
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* Fixed bug where `tune_cluster()` would error if used with an recipe that contained non-predictor variables such as id variables. (#124)
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* Cluster reordering is now done at the fitting time, not the extraction and prediction time. (#154)
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## Breaking Changes
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* Engine specific documentation has been added for all models and engines. (#159)
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* Fixed bug where levels didn't match number of clusters if prediction on fewer number of observations. (#158)
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* Exported internal functions `ClusterR_kmeans_fit()`, `stats_kmeans_fit()`, and `hclust_fit()` have been renamed to `.k_means_fit_ClusterR()`, `.k_means_fit_stats()`, and `.hier_clust_fit_stats()` to reduce visibility for users.
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* Fixed bug where `tune_cluster()` would error if used with an recipe that contained non-predictor variables such as id variables. (#124)
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* Cluster reordering is now done at the fitting time, not the extraction and prediction time. (#154)
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# tidyclust 0.1.2
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‎R/engine_docs.R

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#' Knit engine-specific documentation
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#' @param pattern A regular expression to specify which files to knit. The
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#' default knits all engine documentation files.
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#' @param ... Options passed to [knitr::knit()].
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#' @return A tibble with column `file` for the file name and `result` (a
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#' character vector that echos the output file name or, when there is
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#' a failure, the error message).

‎R/hier_clust.R

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#'
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#' @param x matrix or data frame
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#' @param num_clusters the number of clusters
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#' @param h the height to cut the dendrogram
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#' @param cut_height the height to cut the dendrogram
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#' @param linkage_method the agglomeration method to be used. This should be (an
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#' unambiguous abbreviation of) one of `"ward.D"`, `"ward.D2"`, `"single"`,
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#' `"complete"`, `"average"` (= UPGMA), `"mcquitty"` (= WPGMA), `"median"` (=

‎README.md

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set.seed(1234)
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kmeans_spec <- k_means(num_clusters = 3) %>%
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set_engine("stats")
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set_engine("stats")
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kmeans_spec
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#> K Means Cluster Specification (partition)
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kmeans_spec_fit
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#> tidyclust cluster object
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#>
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#> K-means clustering with 3 clusters of sizes 7, 14, 11
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#> K-means clustering with 3 clusters of sizes 7, 11, 14
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#>
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#> Cluster means:
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#> mpg cyl disp hp drat wt qsec vs
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#> 1 19.74286 6 183.3143 122.28571 3.585714 3.117143 17.97714 0.5714286
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#> 2 15.10000 8 353.1000 209.21429 3.229286 3.999214 16.77214 0.0000000
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#> 3 26.66364 4 105.1364 82.63636 4.070909 2.285727 19.13727 0.9090909
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#> 2 15.10000 8 353.1000 209.21429 3.229286 3.999214 16.77214 0.0000000
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#> am gear carb
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#> 1 0.4285714 3.857143 3.428571
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#> 2 0.1428571 3.285714 3.500000
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#> 3 0.7272727 4.090909 1.545455
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#> 2 0.1428571 3.285714 3.500000
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#>
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#> Clustering vector:
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#> Mazda RX4 Mazda RX4 Wag Datsun 710 Hornet 4 Drive
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#> 1 1 3 1
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#> 1 1 2 1
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#> Hornet Sportabout Valiant Duster 360 Merc 240D
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#> 2 1 2 3
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#> 3 1 3 2
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#> Merc 230 Merc 280 Merc 280C Merc 450SE
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#> 3 1 1 2
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#> 2 1 1 3
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#> Merc 450SL Merc 450SLC Cadillac Fleetwood Lincoln Continental
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#> 2 2 2 2
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#> 3 3 3 3
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#> Chrysler Imperial Fiat 128 Honda Civic Toyota Corolla
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#> 2 3 3 3
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#> Toyota Corona Dodge Challenger AMC Javelin Camaro Z28
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#> 3 2 2 2
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#> Pontiac Firebird Fiat X1-9 Porsche 914-2 Lotus Europa
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#> Toyota Corona Dodge Challenger AMC Javelin Camaro Z28
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#> 2 3 3 3
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#> Pontiac Firebird Fiat X1-9 Porsche 914-2 Lotus Europa
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#> 3 2 2 2
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#> Ford Pantera L Ferrari Dino Maserati Bora Volvo 142E
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#> 2 1 2 3
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#> 3 1 3 2
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#>
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#> Within cluster sum of squares by cluster:
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#> [1] 13954.34 93643.90 11848.37
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#> [1] 13954.34 11848.37 93643.90
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#> (between_SS / total_SS = 80.8 %)
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#>
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#> Available components:
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#> 8 Cluster_2
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#> 9 Cluster_2
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#> 10 Cluster_1
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#> # … with 22 more rows
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#> # ℹ 22 more rows
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```
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and `extract_centroids()` returns the locations of the clusters

‎cran-comments.md

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## Comments
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Patch release to make sure `utils::packageVersion()` doesn't cause issues when package isn't available.
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Release including fix for all known bugs, new engines and better document and error messages.
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## R CMD check results
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‎man/dot-hier_clust_fit_stats.Rd

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