spark-instrumented-optimizer/mllib
zhengruifeng f35f352096 [SPARK-30543][ML][PYSPARK][R] RandomForest add Param bootstrap to control sampling method
### What changes were proposed in this pull request?
add a param `bootstrap` to control whether bootstrap samples are used.

### Why are the changes needed?
Current RF with numTrees=1 will directly build a tree using the orignial dataset,

while with numTrees>1 it will use bootstrap samples to build trees.

This design is for training a DecisionTreeModel by the impl of RandomForest, however, it is somewhat strange.

In Scikit-Learn, there is a param [bootstrap](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier.html#sklearn.ensemble.RandomForestClassifier) to control whether bootstrap samples are used.

### Does this PR introduce any user-facing change?
Yes, new param is added

### How was this patch tested?
existing testsuites

Closes #27254 from zhengruifeng/add_bootstrap.

Authored-by: zhengruifeng <ruifengz@foxmail.com>
Signed-off-by: zhengruifeng <ruifengz@foxmail.com>
2020-01-23 16:44:13 +08:00
..
benchmarks [SPARK-29297][TESTS] Compare core/mllib module benchmarks in JDK8/11 2019-09-29 21:43:58 -07:00
src [SPARK-30543][ML][PYSPARK][R] RandomForest add Param bootstrap to control sampling method 2020-01-23 16:44:13 +08:00
pom.xml [INFRA] Reverts commit 56dcd79 and c216ef1 2019-12-16 19:57:44 -07:00