scala - Difference between org.apache.spark.ml.classification and org.apache.spark.mllib.classification -


i'm writing spark application , use algorithms in mllib. in api doc found 2 different classes same algorithm.

for example, there 1 logisticregression in org.apache.spark.ml.classification logisticregressionwithsgd in org.apache.spark.mllib.classification.

the difference can find 1 in org.apache.spark.ml inherited estimator , able used in cross validation. quite confused placed in different packages. there know reason it? thanks!

it's jira ticket

and design doc:

mllib covers basic selection of machine learning algorithms, e.g., logistic regression, decision trees, alternating least squares, , k-means. current set of apis contains several design flaws prevent moving forward address practical machine learning pipelines, make mllib scalable project.

the new set of apis live under org.apache.spark.ml, , o.a.s.mllib deprecated once migrate features o.a.s.ml.


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