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- SPARK-21245
Resolve code duplication for classification/regression summarizers - SPARK-21152
Use level 3 BLAS operations in LogisticAggregator - SPARK-18060
Avoid unnecessary standardization in multinomial logistic regression training - SPARK-17476
Proper handling for unseen labels in logistic regression training. - SPARK-17201
Investigate numerical instability for MLOR without regularization - SPARK-17163
Merge MLOR into a single LOR interface - SPARK-17151
Decide how to handle inferring number of classes in Multinomial logistic regression - SPARK-17140
Add initial model to MultinomialLogisticRegression - SPARK-17139
Add model summary for MultinomialLogisticRegression - SPARK-17138
Python API for multinomial logistic regression - SPARK-17137
Add compressed support for multinomial logistic regression coefficients - SPARK-17136
Design optimizer interface for ML algorithms - SPARK-17135
Consolidate code in linear/logistic regression where possible - SPARK-17134
Use level 2 BLAS operations in LogisticAggregator - SPARK-17090
Make tree aggregation level in linear/logistic regression configurable
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