The chunks of the matrix representing the linear model
blockSize to split data before applying transformations
optional intercept term to be added
optional seq of transformers to be applied before transformation
Chains a label estimator onto the end of this pipeline, producing a new pipeline.
Chains a label estimator onto the end of this pipeline, producing a new pipeline. If this pipeline has already been executed, it will not need to be fit again.
The estimator to chain onto the end of this pipeline
The training data to use (the estimator will be fit on the result of passing this data through the current pipeline)
The labels to use when fitting the LabelEstimator. Must be zippable with the training data.
Chains a label estimator onto the end of this pipeline, producing a new pipeline.
Chains a label estimator onto the end of this pipeline, producing a new pipeline. If this pipeline has already been executed, it will not need to be fit again.
The estimator to chain onto the end of this pipeline
The training data to use (the estimator will be fit on the result of passing this data through the current pipeline)
The labels to use when fitting the LabelEstimator. Must be zippable with the training data.
Chains a label estimator onto the end of this pipeline, producing a new pipeline.
Chains a label estimator onto the end of this pipeline, producing a new pipeline. If this pipeline has already been executed, it will not need to be fit again.
The estimator to chain onto the end of this pipeline
The training data to use (the estimator will be fit on the result of passing this data through the current pipeline)
The labels to use when fitting the LabelEstimator. Must be zippable with the training data.
Chains a label estimator onto the end of this pipeline, producing a new pipeline.
Chains a label estimator onto the end of this pipeline, producing a new pipeline. If this pipeline has already been executed, it will not need to be fit again.
The estimator to chain onto the end of this pipeline
The training data to use (the estimator will be fit on the result of passing this data through the current pipeline)
The labels to use when fitting the LabelEstimator. Must be zippable with the training data.
Chains an estimator onto the end of this pipeline, producing a new pipeline.
Chains an estimator onto the end of this pipeline, producing a new pipeline. If this pipeline has already been executed, it will not need to be fit again.
The estimator to chain onto the end of this pipeline
The training data to use (the estimator will be fit on the result of passing this data through the current pipeline)
Chains an estimator onto the end of this pipeline, producing a new pipeline.
Chains an estimator onto the end of this pipeline, producing a new pipeline. If this pipeline has already been executed, it will not need to be fit again.
The estimator to chain onto the end of this pipeline
The training data to use (the estimator will be fit on the result of passing this data through the current pipeline)
Chains a pipeline onto the end of this one, producing a new pipeline.
Chains a pipeline onto the end of this one, producing a new pipeline. If either this pipeline or the following has already been executed, it will not need to be fit again.
the pipeline to chain
The application of this Transformer to a single input item.
The application of this Transformer to a single input item. This method MUST be overridden by ML developers.
The input item to pass into this transformer
The output value
Applies the linear model to feature vectors large enough to have been split into several RDDs.
Applies the linear model to feature vectors large enough to have been split into several RDDs.
the output vectors
Applies the linear model to feature vectors large enough to have been split into several RDDs.
Applies the linear model to feature vectors large enough to have been split into several RDDs.
RDD of vectors to apply the model to
the output vectors
Applies the linear model to feature vectors.
Applies the linear model to feature vectors. After processing chunk i of every vector, applies
sequence of input RDD chunks
to the intermediate output vector.
Applies the linear model to feature vectors.
Applies the linear model to feature vectors. After processing chunk i of every vector, applies
input RDD
to the intermediate output vector.
optional intercept term to be added
blockSize to split data before applying transformations
optional seq of transformers to be applied before transformation
A method that converts this object into a Pipeline.
A method that converts this object into a Pipeline. Must be implemented by anything that extends Chainable.
The chunks of the matrix representing the linear model
Transformer that applies a linear model to an input. Different from LinearMapper in that the matrix representing the transformation is split into a seq.