In the `spark.mllib` package, there were several breaking changes. The first change (in `ALS`) is the only one in a component not marked as Alpha or Experimental.
* *(Breaking change)* In [`ALS`](api/scala/index.html#org.apache.spark.mllib.recommendation.ALS), the extraneous method `solveLeastSquares` has been removed. The `DeveloperApi` method `analyzeBlocks` was also removed.
* *(Breaking change)* [`StandardScalerModel`](api/scala/index.html#org.apache.spark.mllib.feature.StandardScalerModel) remains an Alpha component. In it, the `variance` method has been replaced with the `std` method. To compute the column variance values returned by the original `variance` method, simply square the standard deviation values returned by `std`.
* *(Breaking change)* [`StreamingLinearRegressionWithSGD`](api/scala/index.html#org.apache.spark.mllib.regression.StreamingLinearRegressionWithSGD) remains an Experimental component. In it, there were two changes:
* The constructor taking arguments was removed in favor of a builder pattern using the default constructor plus parameter setter methods.
* Variable `model` is no longer public.
* *(Breaking change)* [`DecisionTree`](api/scala/index.html#org.apache.spark.mllib.tree.DecisionTree) remains an Experimental component. In it and its associated classes, there were several changes:
* In `DecisionTree`, the deprecated class method `train` has been removed. (The object/static `train` methods remain.)
* In `Strategy`, the `checkpointDir` parameter has been removed. Checkpointing is still supported, but the checkpoint directory must be set before calling tree and tree ensemble training.
*`PythonMLlibAPI` (the interface between Scala/Java and Python for MLlib) was a public API but is now private, declared `private[python]`. This was never meant for external use.
* In linear regression (including Lasso and ridge regression), the squared loss is now divided by 2.
So in order to produce the same result as in 1.2, the regularization parameter needs to be divided by 2 and the step size needs to be multiplied by 2.
or via [`DecisionTree`](api/scala/index.html#org.apache.spark.mllib.tree.DecisionTree)
static `trainClassifier` and `trainRegressor` methods.
2.*(Breaking change)* The API for
[`Node`](api/scala/index.html#org.apache.spark.mllib.tree.model.Node) has changed.
This should generally not affect user code, unless the user manually constructs decision trees
(instead of using the `trainClassifier` or `trainRegressor` methods).
The tree `Node` now includes more information, including the probability of the predicted label
(for classification).
3. Printing methods' output has changed. The `toString` (Scala/Java) and `__repr__` (Python) methods used to print the full model; they now print a summary. For the full model, use `toDebugString`.
Examples in the Spark distribution and examples in the
[Decision Trees Guide](mllib-decision-tree.html#examples) have been updated accordingly.