Man pages for USCbiostats/partition
Agglomerative Partitioning Framework for Dimension Reduction

all_columns_reducedCheck if all variables reduced to a single composite
all_doneMark the partition as complete to stop search
append_mappingsAppend a new variable to mapping and filter out composite...
as_directorCreate a custom director
as_measureCreate a custom metric
as_partitionReturn a partition object
as_partitionerCreate a partitioner
as_partition_helpersProcess mapping key to return from 'partition()'
as_partition_stepCreate a partition object from a data frame
as_reducerCreate a custom reducer
assign_partitionProcess a dataset with a partitioner
binary_k_searchSearch for best 'k' using the binary search method
build_next_nameCreate new variable name based on prefix and previous...
calculate_new_variableCalculate or retrieve stored reduced variable
compare_kAssess 'k' search
compare_metricCompare metric to threshold
corrEfficiently fit correlation coefficient for matrix or two...
direct_distanceTarget based on minimum distance matrix
direct_k_clusterTarget based on K-means clustering
direct_measure_reduceApply a partitioner
filter_reducedFilter the reduced mappings
find_min_distance_variablesFind the index of the pair with the smallest distance
fit_distance_matrixFit a distance matrix using correlation coefficients
guess_init_kGuess initial 'k' based on threshold and 'p'
handle_missingProcess reduced variables when missing data
hitsCount and retrieve the number of metrics below threshold
iccCalculate the intraclass correlation coefficient
icc_rCalculate the intraclass correlation coefficient
is_partitionIs this object a partition?
is_partitionerIs this object a partitioner?
is_partition_stepIs this object a 'partition_step'?
is_same_functionAre two functions the same?
k_exhaustedHave all values of 'k' been checked for metric?
kmeans_helpersWhich kmeans algorithm to use?
linear_k_searchSearch for best 'k' using the linear search method
map_partitionMap a partition across a range of minimum information
mapping_helpersSummarize and map partitions and permutations
mapping_keyReturn partition mapping key
matrix_is_exhaustedHave all pairs of variables been checked for metric?
measure_iccMeasure the information loss of reduction using intraclass...
measure_min_iccMeasure the information loss of reduction using the minimum...
measure_min_r2Measure the information loss of reduction using minimum...
measure_std_mutualinfoMeasure the information loss of reduction using standardized...
measure_variance_explainedMeasure the information loss of reduction using the variance...
mutual_informationCalculate the standardized mutual information of a data set
part_iccPartitioner: distance, ICC, scaled means
partitionAgglomerative partitioning
partition_scoresReturn the reduced data from a partition
part_kmeansPartitioner: K-means, ICC, scaled means
part_minr2Partitioner: distance, minimum R-squared, scaled means
part_pc1Partitioner: distance, first principal component, scaled...
part_stdmiPartitioner: distance, mutual information, scaled means
paste_partitionersLookup partitioner types to print in English
permute_dfPermute a data set
pipePipe operator
plot_partitionsPlot partitions
plot_permutationPlot permutation tests
print_colorPrint to the console in color
print_helpersHelper functions to print 'partition' summary
pull_mappingsAccess mapping variables
reduce_first_componentReduce selected variables to first principal component
reduce_kmeansReduce selected variables to scaled means
reduce_mappingsCreate a mapping key out of a list of targets
reduce_scaled_meanReduce selected variables to scaled means
reduce_targetReduce a target
replace_partitionerReplace the director, metric, or reducer for a partitioner
return_if_singleReduce targets if more than one variable, return otherwise
rewind_targetSet target to last value
scaled_meanAverage and scale rows in a 'data.frame'
search_kSearch for the best 'k'
simplify_namesSimplify reduced variable names
simulate_block_dataSimulate correlated blocks of variables
test_permutationPermute partitions
update_distOnly fit the distances for a new variable
USCbiostats/partition documentation built on Oct. 13, 2019, 3:10 p.m.