all_columns_reduced | Check if all variables reduced to a single composite |
all_done | Mark the partition as complete to stop search |
append_mappings | Append a new variable to mapping and filter out composite... |
as_director | Create a custom director |
as_measure | Create a custom metric |
as_partition | Return a partition object |
as_partitioner | Create a partitioner |
as_partition_helpers | Process mapping key to return from 'partition()' |
as_partition_step | Create a partition object from a data frame |
as_reducer | Create a custom reducer |
assign_partition | Process a dataset with a partitioner |
baxter_data | Microbiome data |
binary_k_search | Search for best 'k' using the binary search method |
build_next_name | Create new variable name based on prefix and previous... |
calculate_new_variable | Calculate or retrieve stored reduced variable |
compare_k | Assess 'k' search |
compare_metric | Compare metric to threshold |
corr | Efficiently fit correlation coefficient for matrix or two... |
direct_distance | Target based on minimum distance matrix |
direct_k_cluster | Target based on K-means clustering |
direct_measure_reduce | Apply a partitioner |
filter_reduced | Filter the reduced mappings |
find_min_distance_variables | Find the index of the pair with the smallest distance |
fit_distance_matrix | Fit a distance matrix using correlation coefficients |
guess_init_k | Guess initial 'k' based on threshold and 'p' |
handle_missing | Process reduced variables when missing data |
hits | Count and retrieve the number of metrics below threshold |
icc | Calculate the intraclass correlation coefficient |
icc_r | Calculate the intraclass correlation coefficient |
is_partition | Is this object a partition? |
is_partitioner | Is this object a partitioner? |
is_partition_step | Is this object a 'partition_step'? |
is_same_function | Are two functions the same? |
k_exhausted | Have all values of 'k' been checked for metric? |
kmeans_helpers | Which kmeans algorithm to use? |
linear_k_search | Search for best 'k' using the linear search method |
map_partition | Map a partition across a range of minimum information |
mapping_helpers | Summarize and map partitions and permutations |
mapping_key | Return partition mapping key |
matrix_is_exhausted | Have all pairs of variables been checked for metric? |
measure_icc | Measure the information loss of reduction using intraclass... |
measure_min_icc | Measure the information loss of reduction using the minimum... |
measure_min_r2 | Measure the information loss of reduction using minimum... |
measure_std_mutualinfo | Measure the information loss of reduction using standardized... |
measure_variance_explained | Measure the information loss of reduction using the variance... |
mutual_information | Calculate the standardized mutual information of a data set |
part_icc | Partitioner: distance, ICC, scaled means |
partition | Agglomerative partitioning |
partition_scores | Return the reduced data from a partition |
part_kmeans | Partitioner: K-means, ICC, scaled means |
part_minr2 | Partitioner: distance, minimum R-squared, scaled means |
part_pc1 | Partitioner: distance, first principal component, scaled... |
part_stdmi | Partitioner: distance, mutual information, scaled means |
paste_partitioners | Lookup partitioner types to print in English |
permute_df | Permute a data set |
pipe | Pipe operator |
plot_partitions | Plot partitions |
plot_permutation | Plot permutation tests |
print_color | Print to the console in color |
print_helpers | Helper functions to print 'partition' summary |
pull_mappings | Access mapping variables |
reduce_first_component | Reduce selected variables to first principal component |
reduce_kmeans | Reduce selected variables to scaled means |
reduce_mappings | Create a mapping key out of a list of targets |
reduce_scaled_mean | Reduce selected variables to scaled means |
reduce_target | Reduce a target |
replace_partitioner | Replace the director, metric, or reducer for a partitioner |
return_if_single | Reduce targets if more than one variable, return otherwise |
rewind_target | Set target to last value |
scaled_mean | Average and scale rows in a 'data.frame' |
search_k | Search for the best 'k' |
simplify_names | Simplify reduced variable names |
simulate_block_data | Simulate correlated blocks of variables |
super_partition | super_partition |
test_permutation | Permute partitions |
update_dist | Only fit the distances for a new variable |
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.