com.salesforce.op.stages.impl.selector
SelectedModelCombiner
Related Doc: package selector
name of operation
stage uid
Input Features type
Input Features type
Checks the input length
Checks the input length
input features
true is input size as expected, false otherwise
Check if the stage is serializable
Check if the stage is serializable
Failure if not serializable
This method is used to make a copy of the instance with new parameters in several methods in spark internals Default will find the constructor and make a copy for any class (AS LONG AS ALL CONSTRUCTOR PARAMS ARE VALS, this is why type tags are written as implicit vals in base classes).
This method is used to make a copy of the instance with new parameters in several methods in spark internals Default will find the constructor and make a copy for any class (AS LONG AS ALL CONSTRUCTOR PARAMS ARE VALS, this is why type tags are written as implicit vals in base classes).
Note: that the convention in spark is to have the uid be a constructor argument, so that copies will share a uid with the original (developers should follow this convention).
new parameters want to add to instance
a new instance with the same uid
Function that evaluates the selected model on the test set
Function that evaluates the selected model on the test set
data transformed by best model
EvaluationMetrics
Gets an input feature Note: this method IS NOT safe to use outside the driver, please use getTransientFeature method instead
Gets an input feature Note: this method IS NOT safe to use outside the driver, please use getTransientFeature method instead
array of features
NoSuchElementException if the features are not set
RuntimeException in case one of the features is null
Gets the input features Note: this method IS NOT safe to use outside the driver, please use getTransientFeatures method instead
Gets the input features Note: this method IS NOT safe to use outside the driver, please use getTransientFeatures method instead
array of features
NoSuchElementException if the features are not set
RuntimeException in case one of the features is null
Output features that will be created by this stage
Output features that will be created by this stage
feature of type OutputFeatures
Name of output feature (i.e.
Name of output feature (i.e. column created by this stage)
Gets an input feature at index i
Gets an input feature at index i
input index
maybe an input feature
Gets the input Features
Function to convert InputFeatures to an Array of FeatureLike
Function to convert InputFeatures to an Array of FeatureLike
an Array of FeatureLike
Function to be called on getMetadata
Function to be called on getMetadata
Function to be called on setInput
Function to be called on setInput
name of operation
name of operation
Function to convert OutputFeatures to an Array of FeatureLike
Function to convert OutputFeatures to an Array of FeatureLike
an Array of FeatureLike
Should output feature be a response? Yes, if any of the input features are.
Should output feature be a response? Yes, if any of the input features are.
true if the the output feature should be a response
Input features that will be used by the stage
Input features that will be used by the stage
feature of type InputFeatures
Sets input features
Sets input features
feature like type
array of input features
this stage
Stage unique name consisting of the stage operation name and uid
Stage unique name consisting of the stage operation name and uid
stage name
This function translates the input and output features into spark schema checks and changes that will occur on the underlying data frame
This function translates the input and output features into spark schema checks and changes that will occur on the underlying data frame
schema of the input data frame
a new schema with the output features added
Type tag of the output
Type tag of the output
Type tag of the output value
Type tag of the output value
stage uid
stage uid
Class used to combine the predictions produced by two model selectors into a single prediction. Does this by either taking the best models prediction or a combination of the two predictions that is either weighted by the accuracy measure or equal. Uses the summary information from the model selectors to determine the accuracy of the predictions and reruns evaluation (both train and test) when the predictions are combined.