Clustering via Quadratic Scoring

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Documentation for package ‘qcluster’ version 3.0.0

• DESCRIPTION file
• Package NEWS

Help Pages

apply_method	Fit a Single Method From a Method Set
banknote	Swiss Banknotes Data
clust2params	Converts Hard Assignment Into Cluster Parameters
gmix	Gaussian Mixture Modelling
mbind	Combines Methods Settings
mset_gmix	Generates Methods Settings for Gaussian Mixture Model-Based Clustering
mset_kmeans	Generates Methods Settings for K-Means Clustering
mset_pam	Generates Methods Settings for Partitioning Around Medoids (Pam) Clustering
mset_screen	Two-Step Method-Set Preselection Filter
mset_tmix	Generates Methods Settings for Student-t Mixture Model-Based Clustering
mset_user	Generates Clustering Methods Settings for a Prototype Methodology Provided by the User
plot.gmix	Plot Fitted Mixture Models
plot.qcluster	Plot Held-Out Quadratic Score Results
plot.tmix	Plot Fitted Mixture Models
plot_clustering	Plot Data With Clustering Information
predict.gmix	Predict Cluster Assignments From a Fitted Mixture Model
predict.tmix	Predict Cluster Assignments From a Fitted Mixture Model
print.apply_method	Print a Fitted Method (apply_method Result)
print.mset_screen	Display a Summary of a Method-Set Screening Result
print.qcfit	Display Information for Mixture Model Objects
print.qcluster	Display Information on Held-Out Quadratic Score Objects
print.qcmethod	Display a Compact Summary of a Method Set
qcluster	Held-Out Validation of Clustering Solutions by Quadratic Scoring
qcluster_rank	Ranking Clustering Solutions Scored by Held-Out Validation
qcluster_select	Select Ranked Clustering Solutions by Held-Out Quadratic Score
qscore	Clustering Quadratic Score
summary.qcmethod	Inspect a Method Set or a Single Method
tmix	Student-t Mixture Modelling