Class: AFTSurvivalRegressionModel

eclairjs/ml/regression. AFTSurvivalRegressionModel

new AFTSurvivalRegressionModel()

:: Experimental :: Model produced by AFTSurvivalRegression.
Source:

Methods

(static) load(path) → {module:eclairjs/ml/regression.AFTSurvivalRegressionModel}

Parameters:
Name Type Description
path string
Source:
Returns:
Type
module:eclairjs/ml/regression.AFTSurvivalRegressionModel

(static) read() → {MLReader}

Source:
Returns:
Type
MLReader

censorCol() → {module:eclairjs/ml/param.Param}

Param for censor column name. The value of this column could be 0 or 1. If the value is 1, it means the event has occurred i.e. uncensored; otherwise censored.
Source:
Returns:
Type
module:eclairjs/ml/param.Param

coefficients() → {module:eclairjs/mllib/linalg.Vector}

Source:
Returns:
Type
module:eclairjs/mllib/linalg.Vector

copy(extra) → {module:eclairjs/ml/regression.AFTSurvivalRegressionModel}

Parameters:
Name Type Description
extra module:eclairjs/ml/param.ParamMap
Source:
Returns:
Type
module:eclairjs/ml/regression.AFTSurvivalRegressionModel

getCensorCol() → {string}

Source:
Returns:
Type
string

getQuantileProbabilities() → {Array.<float>}

Source:
Returns:
Type
Array.<float>

getQuantilesCol() → {string}

Source:
Returns:
Type
string

hasQuantilesCol() → {boolean}

Checks whether the input has quantiles column name.
Source:
Returns:
Type
boolean

intercept() → {flaot}

Source:
Returns:
Type
flaot

predict(features) → {float}

Parameters:
Name Type Description
features module:eclairjs/mllib/linalg.Vector
Source:
Returns:
Type
float

predictQuantiles(features) → {module:eclairjs/mllib/linalg.Vector}

Parameters:
Name Type Description
features module:eclairjs/mllib/linalg.Vector
Source:
Returns:
Type
module:eclairjs/mllib/linalg.Vector

quantileProbabilities() → {DoubleArrayParam}

Param for quantile probabilities array. Values of the quantile probabilities array should be in the range (0, 1) and the array should be non-empty.
Source:
Returns:
Type
DoubleArrayParam

quantilesCol() → {module:eclairjs/ml/param.Param}

Param for quantiles column name. This column will output quantiles of corresponding quantileProbabilities if it is set.
Source:
Returns:
Type
module:eclairjs/ml/param.Param

scale() → {flaot}

Source:
Returns:
Type
flaot

setFeaturesCol(value) → {module:eclairjs/ml/regression.AFTSurvivalRegressionModel}

Parameters:
Name Type Description
value string
Source:
Returns:
Type
module:eclairjs/ml/regression.AFTSurvivalRegressionModel

setPredictionCol(value) → {module:eclairjs/ml/regression.AFTSurvivalRegressionModel}

Parameters:
Name Type Description
value string
Source:
Returns:
Type
module:eclairjs/ml/regression.AFTSurvivalRegressionModel

setQuantileProbabilities(value) → {module:eclairjs/ml/regression.AFTSurvivalRegressionModel}

Parameters:
Name Type Description
value Array.<float>
Source:
Returns:
Type
module:eclairjs/ml/regression.AFTSurvivalRegressionModel

setQuantilesCol(value) → {module:eclairjs/ml/regression.AFTSurvivalRegressionModel}

Parameters:
Name Type Description
value string
Source:
Returns:
Type
module:eclairjs/ml/regression.AFTSurvivalRegressionModel

transform(dataset) → {module:eclairjs/sql.Dataset}

Parameters:
Name Type Description
dataset module:eclairjs/sql.Dataset
Source:
Returns:
Type
module:eclairjs/sql.Dataset

transformSchema(schema) → {module:eclairjs/sql/types.StructType}

Parameters:
Name Type Description
schema module:eclairjs/sql/types.StructType
Source:
Returns:
Type
module:eclairjs/sql/types.StructType

uid() → {string}

An immutable unique ID for the object and its derivatives.
Source:
Returns:
Type
string

validateAndTransformSchema(schema, fitting) → {module:eclairjs/sql/types.StructType}

Validates and transforms the input schema with the provided param map.
Parameters:
Name Type Description
schema module:eclairjs/sql/types.StructType input schema
fitting boolean whether this is in fitting or prediction
Source:
Returns:
Type
module:eclairjs/sql/types.StructType

write() → {MLWriter}

Source:
Returns:
Type
MLWriter