[SPARK-10413] ML models should support prediction on single instances - ASF JIRA

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Currently models in the pipeline API only implement transform(DataFrame). It would be quite useful to support prediction on single instance.

UPDATE: This issue is for making predictions with single models. We can make methods like def predict(features: Vector): Double public.

This issue is not for single-instance prediction for full Pipelines, which would require making predictions on {{Row}}s.

Is contained by

SPARK-14377 Review spark.ml parity for classification, except trees

is related to

SPARK-30358 ML expose predictRaw and predictProbability

SPARK-16365 Ideas for moving "mllib-local" forward

relates to

SPARK-16431 Add a unified method that accepts single instances to feature transformers and predictors

SPARK-5874 How to improve the current ML pipeline API?

1.	Support prediction on single instance for regression and classification related models		Resolved	Weichen Xu
2.	Support prediction on single instance in KMeans/BiKMeans/GMM		Resolved	Ruifeng Zheng