rtemis (version 0.79)

u.H2OKMEANS: K-Means Clustering on H2O

Description

K-Means clustering using h2o::h2o.kmeans Check out the H2O Flow at [ip]:[port], Default IP:port is "localhost:54321" e.g. if running on localhost, point your web browser to localhost:54321

Usage

u.H2OKMEANS(x, x.test = NULL, k = 2, estimate.k = FALSE,
  nfolds = 0, max.iterations = 10, ip = "localhost", port = 54321,
  n.cores = rtCores, seed = -1, init = c("Furthest", "Random",
  "PlusPlus", "User"), categorical.encoding = c("AUTO", "Enum",
  "OneHotInternal", "OneHotExplicit", "Binary", "Eigen", "LabelEncoder",
  "SortByResponse", "EnumLimited"), verbose = TRUE, ...)

Arguments

x

Input matrix / data.frame

x.test

Testing set matrix / data.frame

k

Integer: Number of clusters to get

estimate.k

Logical: if TRUE, estimate k up to a maximum set by the k argument

nfolds

Integer: Number of cross-validation folds

max.iterations

Integer: Maximum number of iterations

ip

String: IP address of H2O server. Default = "localhost"

port

Integer: Port number of H2O server. Default = 54321

n.cores

Integer: Number of cores to use

seed

Integer: Seed for H2O's random number generator. Default = -1 (time-based ranodm number)

init

String: Initialization mode: "Furthest", "Random", "PlusPlus", "User". Default = "Furthest"

categorical.encoding

String: How to encode categorical variables: "AUTO", "Enum", "OneHotInternal", "OneHotExplicit", "Binary", "Eigen", "LabelEncoder", "SortByResponse", "EnumLimited". Default = "AUTO"

verbose

Logical: If TRUE, print messages to screen

...

Additional arguments to pass to h2p::h2o.kmeans

Value

rtMod object

Details

For additional information, see help on h2o::h2o.kmeans

See Also

Other Clustering: u.CMEANS, u.EMC, u.HARDCL, u.HOPACH, u.KMEANS, u.NGAS, u.PAMK, u.PAM, u.SPEC