The Estimator class, just like the Transformer class, was introduced in Spark 1.3. The Estimators, as the name suggests, estimate the parameters of a model or, in other words, fit the models to data.
In this recipe, we will introduce two models: the linear SVM acting as a classification model, and a linear regression model predicting the forest elevation.
Here is a list of all of the Estimators, or machine learning models, available in the ML module:
- Classification:
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LinearSVC is an SVM model for linearly separable problems. The SVM's kernel has the
form (a hyperplane), where 
is the coefficients (or a normal vector to the hyperplane), 
is the records, and b is the offset. -
LogisticRegression is a default, go-to classification model for linearly separable problems. It uses a logit function...
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