fsml_hclust Interface

public interface fsml_hclust

The procedure is an implementation of the agglomerative hierarchical clustering method that groups data points into clusters by iteratively merging the most similar clusters. The procedure uses centroid linkage and the Mahalanobis distance as a measure of similarity.

The input matrix (x) holds observations in rows (nd) and variables in columns (nv). The target number of clusters (nc) must be at least 1 and not greater than the number of data points.

The variables are standardised before computing the covariance matrix on the transformed data. The matrix is used for calculating the Mahalanobis distance.

Clusters are merged iteratively until the target number of clusters is reached. The global mean (gm), cluster centroids (cm), membership assignments (cl), and cluster sizes (cc), the covariance matrix (cov) and standard deviations (sigma) used in the distance calculations are returned.

Calls

interface~~fsml_hclust~~CallsGraph interface~fsml_hclust fsml_hclust proc~s_nlp_hclust s_nlp_hclust interface~fsml_hclust->proc~s_nlp_hclust proc~s_err_print s_err_print proc~s_nlp_hclust->proc~s_err_print proc~s_err_warn s_err_warn proc~s_nlp_hclust->proc~s_err_warn proc~s_nlp_hclust_core s_nlp_hclust_core proc~s_nlp_hclust->proc~s_nlp_hclust_core proc~f_utl_r2c f_utl_r2c proc~s_err_print->proc~f_utl_r2c proc~s_err_warn->proc~f_utl_r2c proc~f_lin_mahalanobis_core f_lin_mahalanobis_core proc~s_nlp_hclust_core->proc~f_lin_mahalanobis_core proc~f_sts_cov_core f_sts_cov_core proc~s_nlp_hclust_core->proc~f_sts_cov_core proc~f_sts_mean_core f_sts_mean_core proc~s_nlp_hclust_core->proc~f_sts_mean_core proc~f_sts_var_core f_sts_var_core proc~s_nlp_hclust_core->proc~f_sts_var_core proc~s_utl_sort s_utl_sort proc~s_nlp_hclust_core->proc~s_utl_sort proc~f_lin_mahalanobis_core->proc~f_sts_cov_core proc~s_utl_cholesky_solve s_utl_cholesky_solve proc~f_lin_mahalanobis_core->proc~s_utl_cholesky_solve proc~f_sts_cov_core->proc~f_sts_mean_core proc~f_sts_var_core->proc~f_sts_mean_core chol chol proc~s_utl_cholesky_solve->chol

Module Procedures

public impure subroutine s_nlp_hclust(x, nd, nv, nc, gm, cm, cl, cc, cov, sigma)

Impure wrapper procedure for s_nlp_hclust_core.

Arguments

Type IntentOptional Attributes Name
real(kind=wp), intent(in) :: x(nd,nv)

input data matrix (samples, variables)
integer(kind=i4), intent(in) :: nd

number of data points
integer(kind=i4), intent(in) :: nv

number of variables
integer(kind=i4), intent(in) :: nc

number of clusters (target)
real(kind=wp), intent(out) :: gm(nv)

global means for each variable
real(kind=wp), intent(out) :: cm(nv,nc)

cluster centroids
integer(kind=i4), intent(out) :: cl(nd)

cluster assignments for each data point
integer(kind=i4), intent(out) :: cc(nc)

cluster sizes
real(kind=wp), intent(out) :: cov(nv,nv)

covariance matrix
real(kind=wp), intent(out) :: sigma(nv)

standard deviation per variable