Function reference • galgoR

All functions
`calculate_distance_pearson_gpu()` `calculate_distance_spearman_gpu()` `calculate_distance_uncentered_gpu()` `calculate_distance_euclidean_gpu()` `calculate_distance_pearson_cpu()` `calculate_distance_spearman_cpu()` `calculate_distance_uncentered_cpu()` `calculate_distance_euclidean_cpu()` `select_distance()`	Functions to calculate distance matrices using cpu or gpu computing
`classify()`	Distance to centroid classifier function
`classify_multiple()`	Classify samples from multiple centroids
`cluster_algorithm()`	Wrapper function to perform partition around medioids (PAM) for GalgoR
`cosine()`	Function for calculating the cosine similarity
`create_centroids()`	Create Centroids
`fitness()`	Survival fitness function using the Restricted Mean Survival Time (RMST) of each group
`galgo.Obj-class`	Galgo Object class
`galgo()`	GalgoR main function
`galgoR-package`	GalgoR: A bi-objective evolutionary meta-heuristic to identify robust transcriptomic classifiers associated with patient outcome across multiple cancer types.
`kcentroid()`	Function to calculate the centroids of different groups (classes)
`non_dominated_summary()`	Summary of the non dominated solutions
`plot_pareto()`	Plot pareto front from an galgo.Obj
`toDataFrame()`	Convert galgo.Obj to data.frame
`toList()`	Convert galgo.Obj to list
`use_rna_luad()`	Download a toy dataset to test galgoR

Reference