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partition  

Agglomerative Partitioning Framework for Dimension Reduction
View on CRAN: Click here


Download and install partition package within the R console
Install from CRAN:
install.packages("partition")

Install from Github:
library("remotes")
install_github("cran/partition")

Install by package version:
library("remotes")
install_version("partition", "0.2.2")



Attach the package and use:
library("partition")
Maintained by
Malcolm Barrett
[Scholar Profile | Author Map]
First Published: 2019-05-17
Latest Update: 2024-01-24
Description:
A fast and flexible framework for agglomerative partitioning. 'partition' uses an approach called Direct-Measure-Reduce to create new variables that maintain the user-specified minimum level of information. Each reduced variable is also interpretable: the original variables map to one and only one variable in the reduced data set. 'partition' is flexible, as well: how variables are selected to reduce, how information loss is measured, and the way data is reduced can all be customized. 'partition' is based on the Partition framework discussed in Millstein et al. (2020) .
How to cite:
Malcolm Barrett (2019). partition: Agglomerative Partitioning Framework for Dimension Reduction. R package version 0.2.2, https://cran.r-project.org/web/packages/partition. Accessed 06 Apr. 2025.
Previous versions and publish date:
0.1.0 (2019-05-17 09:00), 0.1.1 (2019-12-12 07:30), 0.1.2 (2020-05-24 23:40), 0.1.3 (2021-01-07 23:30), 0.1.4 (2021-10-05 06:20), 0.2.0 (2024-01-24 20:20), 0.2.1 (2024-05-22 17:40)
Other packages that cited partition R package
View partition citation profile
Other R packages that partition depends, imports, suggests or enhances
Complete documentation for partition
Functions, R codes and Examples using the partition R package
Some associated functions: all_columns_reduced . all_done . append_mappings . as_director . as_measure . as_partition . as_partition_helpers . as_partition_step . as_partitioner . as_reducer . assign_partition . baxter_data . binary_k_search . build_next_name . calculate_new_variable . compare_k . compare_metric . corr . direct_distance . direct_k_cluster . direct_measure_reduce . filter_reduced . find_min_distance_variables . fit_distance_matrix . guess_init_k . handle_missing . hits . icc . icc_r . is_partition . is_partition_step . is_partitioner . is_same_function . k_exhausted . kmeans_helpers . linear_k_search . map_partition . mapping_helpers . mapping_key . matrix_is_exhausted . measure_icc . measure_min_icc . measure_min_r2 . measure_std_mutualinfo . measure_variance_explained . mutual_information . part_icc . part_kmeans . part_minr2 . part_pc1 . part_stdmi . partition . partition_scores . paste_partitioners . permute_df . pipe . plot_partitions . plot_permutation . print_color . print_helpers . pull_mappings . reduce_first_component . reduce_kmeans . reduce_mappings . reduce_scaled_mean . reduce_target . replace_partitioner . return_if_single . rewind_target . scaled_mean . search_k . simplify_names . simulate_block_data . super_partition . test_permutation . update_dist . 
Some associated R codes: RcppExports.R . data.R . directors.R . mappings.R . metrics.R . mutual_information.R . partition.R . partitioners.R . permutation.R . plot.R . print.R . reducers.R . simulate_block.R . super_partition.R . utils-pipe.R . utils.R .  Full partition package functions and examples
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