AFTSurvivalRegressionModel¶
-
class
pyspark.ml.regression.
AFTSurvivalRegressionModel
(java_model=None)[source]¶ Model fitted by
AFTSurvivalRegression
.New in version 1.6.0.
Methods
Attributes
Methods Documentation
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clear
(param)¶ Clears a param from the param map if it has been explicitly set.
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copy
(extra=None)¶ Creates a copy of this instance with the same uid and some extra params. This implementation first calls Params.copy and then make a copy of the companion Java pipeline component with extra params. So both the Python wrapper and the Java pipeline component get copied.
- Parameters
extra – Extra parameters to copy to the new instance
- Returns
Copy of this instance
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explainParam
(param)¶ Explains a single param and returns its name, doc, and optional default value and user-supplied value in a string.
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explainParams
()¶ Returns the documentation of all params with their optionally default values and user-supplied values.
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extractParamMap
(extra=None)¶ Extracts the embedded default param values and user-supplied values, and then merges them with extra values from input into a flat param map, where the latter value is used if there exist conflicts, i.e., with ordering: default param values < user-supplied values < extra.
- Parameters
extra – extra param values
- Returns
merged param map
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getAggregationDepth
()¶ Gets the value of aggregationDepth or its default value.
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getCensorCol
()¶ Gets the value of censorCol or its default value.
New in version 1.6.0.
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getFeaturesCol
()¶ Gets the value of featuresCol or its default value.
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getFitIntercept
()¶ Gets the value of fitIntercept or its default value.
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getLabelCol
()¶ Gets the value of labelCol or its default value.
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getMaxIter
()¶ Gets the value of maxIter or its default value.
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getOrDefault
(param)¶ Gets the value of a param in the user-supplied param map or its default value. Raises an error if neither is set.
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getParam
(paramName)¶ Gets a param by its name.
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getPredictionCol
()¶ Gets the value of predictionCol or its default value.
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getQuantileProbabilities
()¶ Gets the value of quantileProbabilities or its default value.
New in version 1.6.0.
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getQuantilesCol
()¶ Gets the value of quantilesCol or its default value.
New in version 1.6.0.
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getTol
()¶ Gets the value of tol or its default value.
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hasDefault
(param)¶ Checks whether a param has a default value.
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hasParam
(paramName)¶ Tests whether this instance contains a param with a given (string) name.
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isDefined
(param)¶ Checks whether a param is explicitly set by user or has a default value.
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isSet
(param)¶ Checks whether a param is explicitly set by user.
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classmethod
load
(path)¶ Reads an ML instance from the input path, a shortcut of read().load(path).
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predict
(value)¶ Predict label for the given features.
New in version 3.0.0.
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classmethod
read
()¶ Returns an MLReader instance for this class.
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save
(path)¶ Save this ML instance to the given path, a shortcut of ‘write().save(path)’.
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set
(param, value)¶ Sets a parameter in the embedded param map.
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setFeaturesCol
(value)¶ Sets the value of
featuresCol
.New in version 3.0.0.
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setPredictionCol
(value)¶ Sets the value of
predictionCol
.New in version 3.0.0.
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setQuantileProbabilities
(value)[source]¶ Sets the value of
quantileProbabilities
.New in version 3.0.0.
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setQuantilesCol
(value)[source]¶ Sets the value of
quantilesCol
.New in version 3.0.0.
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transform
(dataset, params=None)¶ Transforms the input dataset with optional parameters.
- Parameters
dataset – input dataset, which is an instance of
pyspark.sql.DataFrame
params – an optional param map that overrides embedded params.
- Returns
transformed dataset
New in version 1.3.0.
-
write
()¶ Returns an MLWriter instance for this ML instance.
Attributes Documentation
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aggregationDepth
= Param(parent='undefined', name='aggregationDepth', doc='suggested depth for treeAggregate (>= 2).')¶
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censorCol
= Param(parent='undefined', name='censorCol', doc='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.')¶
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coefficients
¶ Model coefficients.
New in version 2.0.0.
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featuresCol
= Param(parent='undefined', name='featuresCol', doc='features column name.')¶
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fitIntercept
= Param(parent='undefined', name='fitIntercept', doc='whether to fit an intercept term.')¶
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intercept
¶ Model intercept.
New in version 1.6.0.
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labelCol
= Param(parent='undefined', name='labelCol', doc='label column name.')¶
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maxIter
= Param(parent='undefined', name='maxIter', doc='max number of iterations (>= 0).')¶
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numFeatures
¶ Returns the number of features the model was trained on. If unknown, returns -1
New in version 2.1.0.
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params
¶ Returns all params ordered by name. The default implementation uses
dir()
to get all attributes of typeParam
.
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predictionCol
= Param(parent='undefined', name='predictionCol', doc='prediction column name.')¶
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quantileProbabilities
= Param(parent='undefined', name='quantileProbabilities', doc='quantile probabilities array. Values of the quantile probabilities array should be in the range (0, 1) and the array should be non-empty.')¶
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quantilesCol
= Param(parent='undefined', name='quantilesCol', doc='quantiles column name. This column will output quantiles of corresponding quantileProbabilities if it is set.')¶
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scale
¶ Model scale parameter.
New in version 1.6.0.
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tol
= Param(parent='undefined', name='tol', doc='the convergence tolerance for iterative algorithms (>= 0).')¶
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