cox_regression.config module

Configuration parsing and storage for logistic regression

class cox_regression.config.Config(clients, server, data_columns, target_column, intercept, n_epochs, learning_rate, hessian, time_column, n_bins)

Bases: Config

The configuration of the experiment. Contains all attributes of the logistic regression config together with:

Parameters:

• time_column (str) – The column containing event/censoring times

• n_bins (int) – The number of bins to use in stacking

__init__(clients, server, data_columns, target_column, intercept, n_epochs, learning_rate, hessian, time_column, n_bins)

Forwards initialization arguments to parent class.

static from_file(config_path)

Create config from config file

Parameters:

config_path (Path) – The path to the file

Return type:

Config

Returns:

The configuration according to config file

n_bins: int

time_column: str

class cox_regression.config.ConfigParser(config_file_path)

Bases: ConfigParser

Parser for cox regression config file.

Parameters:

• EXPERIMENT_TIME_COLUMN_KEY – Key for which column contains event/censoring times

• EXPERIMENT_N_BINS_KEY – Key for number of bins

EXPERIMENT_N_BINS_COLUMN_KEY = 'n_bins'

EXPERIMENT_TIME_COLUMN_KEY = 'time_column'

__init__(config_file_path)

Load the config file and parse the objects variables from the file.

Parameters:

config_file_path (Path) – The path to the config file

parse_intercept()

In cox regression, an intercept is never used.

Return type:

bool

Returns:

False, indicating no intercept is used.

parse_n_bins()

Parse the number of bins to use in stacking.

Return type:

int

Returns:

the number of bins

Raises:

ValueError – if the number of bins is nonpositive

parse_time_column()

Parse the column containing event/censoring times.

Return type:

str

Returns:

The column containing event/censoring times

to_config()

Convert the parse to an actual config object.

Return type:

Config

Returns:

the config object containing the data from the parsed config file