## What changes were proposed in this pull request?

Cleanup of examples, mostly from PySpark-ML to fix minor issues:  unused imports, style consistency, pipeline_example is a duplicate, use future print funciton, and a spelling error.

* The "Pipeline Example" is duplicated by "Simple Text Classification Pipeline" in Scala, Python, and Java.

* "Estimator Transformer Param Example" is duplicated by "Simple Params Example" in Scala, Python and Java

* Synced random_forest_classifier_example.py with Scala by adding IndexToString label converted

* Synced train_validation_split.py (in Scala ModelSelectionViaTrainValidationExample) by adjusting data split, adding grid for intercept.

* RegexTokenizer was doing nothing in tokenizer_example.py and JavaTokenizerExample.java, synced with Scala version

## How was this patch tested?
local tests and run modified examples

Author: Bryan Cutler <cutlerb@gmail.com>

Closes #14081 from BryanCutler/examples-cleanup-SPARK-16403.

## What changes were proposed in this pull request?
Since [SPARK-15617](https://issues.apache.org/jira/browse/SPARK-15617) deprecated ```precision``` in ```MulticlassClassificationEvaluator```, many ML examples broken.
```python
pyspark.sql.utils.IllegalArgumentException: u'MulticlassClassificationEvaluator_4c3bb1d73d8cc0cedae6 parameter metricName given invalid value precision.'
```
We should use ```accuracy``` to replace ```precision``` in these examples.

## How was this patch tested?
Offline tests.

Author: Yanbo Liang <ybliang8@gmail.com>

Closes #13519 from yanboliang/spark-15771.

[SPARK-15134][EXAMPLE] Indent SparkSession builder patterns and update binary_classification_metrics_example.py

## What changes were proposed in this pull request?

This issue addresses the comments in SPARK-15031 and also fix java-linter errors.
- Use multiline format in SparkSession builder patterns.
- Update `binary_classification_metrics_example.py` to use `SparkSession`.
- Fix Java Linter errors (in SPARK-13745, SPARK-15031, and so far)

## How was this patch tested?

After passing the Jenkins tests and run `dev/lint-java` manually.

Author: Dongjoon Hyun <dongjoon@apache.org>

Closes #12911 from dongjoon-hyun/SPARK-15134.

## What changes were proposed in this pull request?

This PR aims to update Scala/Python/Java examples by replacing `SQLContext` with newly added `SparkSession`.

- Use **SparkSession Builder Pattern** in 154(Scala 55, Java 52, Python 47) files.
- Add `getConf` in Python SparkContext class: `python/pyspark/context.py`
- Replace **SQLContext Singleton Pattern** with **SparkSession Singleton Pattern**:
  - `SqlNetworkWordCount.scala`
  - `JavaSqlNetworkWordCount.java`
  - `sql_network_wordcount.py`

Now, `SQLContexts` are used only in R examples and the following two Python examples. The python examples are untouched in this PR since it already fails some unknown issue.
- `simple_params_example.py`
- `aft_survival_regression.py`

## How was this patch tested?

Manual.

Author: Dongjoon Hyun <dongjoon@apache.org>

Closes #12809 from dongjoon-hyun/SPARK-15031.

JIRA:  https://issues.apache.org/jira/browse/SPARK-13814

## What changes were proposed in this pull request?

delete unnecessary imports in python examples files

## How was this patch tested?

manual tests

Author: Zheng RuiFeng <ruifengz@foxmail.com>

Closes #11651 from zhengruifeng/del_import_pe.

Use LibSVM data source rather than MLUtils.loadLibSVMFile to load DataFrame, include:
* Use libSVM data source for all example codes under examples/ml, and remove unused import.
* Use libSVM data source for user guides under ml-*** which were omitted by #8697.
* Fix bug: We should use ```sqlContext.read().format("libsvm").load(path)``` at Java side, but the API doc and user guides misuse as ```sqlContext.read.format("libsvm").load(path)```.
* Code cleanup.

mengxr

Author: Yanbo Liang <ybliang8@gmail.com>

Closes #9690 from yanboliang/spark-11723.

I have tested it on my local, it is working fine, please review

Author: sachin aggarwal <different.sachin@gmail.com>

Closes #9539 from agsachin/SPARK-11552-real.