Trains a Cox Proportional Hazards Model (CoxPH) on an H2O dataset
Trains a Cox Proportional Hazards Model (CoxPH) on an H2O dataset
h2o.coxph(
x,
event_column,
training_frame,
model_id = NULL,
start_column = NULL,
stop_column = NULL,
weights_column = NULL,
offset_column = NULL,
stratify_by = NULL,
ties = c("efron", "breslow"),
init = 0,
lre_min = 9,
max_iterations = 20,
interactions = NULL,
interaction_pairs = NULL,
interactions_only = NULL,
use_all_factor_levels = FALSE,
export_checkpoints_dir = NULL,
single_node_mode = FALSE
)x |
(Optional) A vector containing the names or indices of the predictor variables to use in building the model. If x is missing, then all columns except event_column, start_column and stop_column are used. |
event_column |
The name of binary data column in the training frame indicating the occurrence of an event. |
training_frame |
Id of the training data frame. |
model_id |
Destination id for this model; auto-generated if not specified. |
start_column |
Start Time Column. |
stop_column |
Stop Time Column. |
weights_column |
Column with observation weights. Giving some observation a weight of zero is equivalent to excluding it from the dataset; giving an observation a relative weight of 2 is equivalent to repeating that row twice. Negative weights are not allowed. Note: Weights are per-row observation weights and do not increase the size of the data frame. This is typically the number of times a row is repeated, but non-integer values are supported as well. During training, rows with higher weights matter more, due to the larger loss function pre-factor. |
offset_column |
Offset column. This will be added to the combination of columns before applying the link function. |
stratify_by |
List of columns to use for stratification. |
ties |
Method for Handling Ties. Must be one of: "efron", "breslow". Defaults to efron. |
init |
Coefficient starting value. Defaults to 0. |
lre_min |
Minimum log-relative error. Defaults to 9. |
max_iterations |
Maximum number of iterations. Defaults to 20. |
interactions |
A list of predictor column indices to interact. All pairwise combinations will be computed for the list. |
interaction_pairs |
A list of pairwise (first order) column interactions. |
interactions_only |
A list of columns that should only be used to create interactions but should not itself participate in model training. |
use_all_factor_levels |
|
export_checkpoints_dir |
Automatically export generated models to this directory. |
single_node_mode |
|
## Not run:
library(h2o)
h2o.init()
# Import the heart dataset
f <- "https://s3.amazonaws.com/h2o-public-test-data/smalldata/coxph_test/heart.csv"
heart <- h2o.importFile(f)
# Set the predictor and response
predictor <- "age"
response <- "event"
# Train a Cox Proportional Hazards model
heart_coxph <- h2o.coxph(x = predictor, training_frame = heart,
event_column = "event",
start_column = "start",
stop_column = "stop")
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.