predict_GMM {ClusterR} | R Documentation |
Prediction function for a Gaussian Mixture Model object
predict_GMM(data, CENTROIDS, COVARIANCE, WEIGHTS)
## S3 method for class 'GMMCluster'
predict(object, newdata, ...)
data |
matrix or data frame |
CENTROIDS |
matrix or data frame containing the centroids (means), stored as row vectors |
COVARIANCE |
matrix or data frame containing the diagonal covariance matrices, stored as row vectors |
WEIGHTS |
vector containing the weights |
object , newdata , ... |
arguments for the 'predict' generic |
This function takes the centroids, covariance matrix and weights from a trained model and returns the log-likelihoods, cluster probabilities and cluster labels for new data.
a list consisting of the log-likelihoods, cluster probabilities and cluster labels.
Lampros Mouselimis
data(dietary_survey_IBS)
dat = as.matrix(dietary_survey_IBS[, -ncol(dietary_survey_IBS)])
dat = center_scale(dat)
gmm = GMM(dat, 2, "maha_dist", "random_subset", 10, 10)
# pr = predict_GMM(dat, gmm$centroids, gmm$covariance_matrices, gmm$weights)