Which of the following statements describes a Spark ML estimator?

Which of the following statements describes a Spark ML estimator?
A . An estimator is a hyperparameter arid that can be used to train a model
B . An estimator chains multiple alqorithms toqether to specify an ML workflow
C . An estimator is a trained ML model which turns a DataFrame with features into a DataFrame with predictions
D . An estimator is an alqorithm which can be fit on a DataFrame to produce a Transformer
E . An estimator is an evaluation tool to assess to the quality of a model

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Answer: D

Explanation:

In the context of Spark MLlib, an estimator refers to an algorithm which can be "fit" on a DataFrame to produce a model (referred to as a Transformer), which can then be used to transform one DataFrame into another, typically adding predictions or model scores. This is a fundamental concept in machine learning pipelines in Spark, where the workflow includes fitting estimators to data to produce transformers.

Reference Spark MLlib Documentation: https://spark.apache.org/docs/latest/ml-pipeline.html#estimators