Specifications

These cluster specification fucntion are used to specify the type of model you want to do. These functions work in a similar fashion to the model specification function from parsnip.

k_means()
K-Means
hier_clust()
Hierarchical (Agglomerative) Clustering

Fit and Inspect

These Functions are the generics are are supported for specifications created with tidyclust.

fit(<cluster_spec>) fit_xy(<cluster_spec>)
Fit a Model Specification to a Data Set
set_args(<cluster_spec>)
Change arguments of a cluster specification
set_engine(<cluster_spec>)
Change engine of a cluster specification
set_mode(<cluster_spec>)
Change mode of a cluster specification
augment(<cluster_fit>)
Augment data with predictions
glance(<cluster_fit>)
Construct a single row summary "glance" of a model, fit, or other object
tidy(<cluster_fit>)
Turn a tidyclust model object into a tidy tibble
extract_fit_engine(<cluster_fit>) extract_parameter_set_dials(<cluster_spec>)
Extract elements of a tidyclust model object

Prediction

Once the cluster specification have been fit, you are likely to want to look at where the clusters are and which observations are associated with which cluster.

predict(<cluster_fit>) predict_raw(<cluster_fit>)
Model predictions
extract_cluster_assignment()
Extract cluster assignments from model
extract_centroids()
Extract clusters from model

Model based performance metrics

These metrics use the fitted clustering model to extract values denoting how well the model works.

cluster_metric_set()
Combine metric functions
silhouette_avg() silhouette_avg_vec()
Measures average silhouette across all observations
sse_ratio() sse_ratio_vec()
Compute the ratio of the WSS to the total SSE
sse_total() sse_total_vec()
Compute the total sum of squares
sse_within_total() sse_within_total_vec()
Compute the sum of within-cluster SSE
silhouette()
Measures silhouette between clusters
sse_within()
Calculates Sum of Squared Error in each cluster

Tuning

Functions to allow multiple cluster specifications to be fit at once.

control_cluster()
Control the fit function
update(<hier_clust>) update(<k_means>)
Update a cluster specification
finalize_model_tidyclust() finalize_workflow_tidyclust()
Splice final parameters into objects
tune_cluster()
Model tuning via grid search

Developer tools

extract_fit_summary()
S3 method to get fitted model summary info depending on engine
get_centroid_dists()
Computes distance from observations to centroids
new_cluster_metric()
Construct a new clustering metric function
prep_data_dist()
Prepares data and distance matrices for metric calculation
reconcile_clusterings_mapping()
Relabels clusters to match another cluster assignment
translate_tidyclust()
Resolve a Model Specification for a Computational Engine
min_grid(<cluster_spec>)
Determine the minimum set of model fits