CoxPhModel train¶

train(self, frame, time_column, covariate_columns, censor_column, convergence_tolerance=1e-06, max_steps=100)¶

[ALPHA] Build Cox proportional hazard model.

Parameters:

Parameters:	frame : Frame A frame to train the model on. time_column : unicode Column containing the time data. covariate_columns : list List of column(s) containing the co-variate data. censor_column : unicode Column containing the censored data. Can have 2 values: 0 - event did not happen (censored); 1 - event happened (not censored) convergence_tolerance : float64 (default=1e-06) Convergence tolerance max_steps : int32 (default=100) Max steps.
Returns:	: dict Trained Cox proportional hazard model

frame : Frame

A frame to train the model on.

time_column : unicode

Column containing the time data.

covariate_columns : list

List of column(s) containing the co-variate data.

censor_column : unicode

Column containing the censored data. Can have 2 values: 0 - event did not happen (censored); 1 - event happened (not censored)

convergence_tolerance : float64 (default=1e-06)

Convergence tolerance

max_steps : int32 (default=100)

Max steps.

Returns:

: dict

Trained Cox proportional hazard model

Fitting a CoxProportionalHazard Model using the covariate column(s)

Examples

See here for examples.