[ https://issues.apache.org/jira/browse/SPARK-7443?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Joseph K. Bradley updated SPARK-7443: ------------------------------------- Description: TODO: create JIRAs for each task and assign them accordingly. h2. API * Check API compliance using java-compliance-checker (SPARK-7458) * Audit new public APIs (from the generated html doc) ** Scala (do not forget to check the object doc) (SPARK-7537) ** Java compatibility (SPARK-7529) ** Python API coverage (SPARK-7536) * audit Pipeline APIs (SPARK-7535) * graduate spark.ml from alpha ** remove AlphaComponent annotations ** remove mima excludes for spark.ml h2. Algorithms and performance *Performance* * _List any other missing performance tests from spark-perf here_ * LDA online/EM (SPARK-7455) * ElasticNet for linear regression and logistic regression (SPARK-7456) * Bernoulli naive Bayes (SPARK-7453) * PIC (SPARK-7454) * ALS.recommendAll (SPARK-7457) * perf-tests in Python (SPARK-7539) *Correctness* * PMML ** scoring using PMML evaluator vs. MLlib models (SPARK-7540) * model save/load (SPARK-7541) h2. Documentation and example code * Create JIRAs for the user guide to each new algorithm and assign them to the corresponding author. Link here as "requires" * Create example code for major components ** cross validation in python ** pipeline with complex feature transformations (scala/java/python) ** elastic-net (possibly with cross validation) was: TODO: create JIRAs for each task and assign them accordingly. h2. API * Check API compliance using java-compliance-checker (SPARK-7458) * Audit new public APIs (from the generated html doc) ** Scala (do not forget to check the object doc) (SPARK-7537) ** Java compatibility (SPARK-7529) ** Python API coverage (SPARK-7536) * audit Pipeline APIs (SPARK-7535) * graduate spark.ml from alpha ** remove AlphaComponent annotations ** remove mima excludes for spark.ml h2. Algorithms and performance *Performance* * _List any other missing performance tests from spark-perf here_ * LDA online/EM (SPARK-7455) * ElasticNet for linear regression and logistic regression (SPARK-7456) * Bernoulli naive Bayes (SPARK-7453) * PIC (SPARK-7454) * ALS.recommendAll (SPARK-7457) * perf-tests in Python (SPARK-7539) *Correctness* * PMML ** scoring using PMML evaluator vs. MLlib models (SPARK-7540) * model save/load h2. Documentation and example code * Create JIRAs for the user guide to each new algorithm and assign them to the corresponding author. Link here as "requires" * Create example code for major components ** cross validation in python ** pipeline with complex feature transformations (scala/java/python) ** elastic-net (possibly with cross validation) > MLlib 1.4 QA plan > ----------------- > > Key: SPARK-7443 > URL: https://issues.apache.org/jira/browse/SPARK-7443 > Project: Spark > Issue Type: Umbrella > Components: ML, MLlib > Affects Versions: 1.4.0 > Reporter: Xiangrui Meng > Assignee: Joseph K. Bradley > Priority: Critical > > TODO: create JIRAs for each task and assign them accordingly. > h2. API > * Check API compliance using java-compliance-checker (SPARK-7458) > * Audit new public APIs (from the generated html doc) > ** Scala (do not forget to check the object doc) (SPARK-7537) > ** Java compatibility (SPARK-7529) > ** Python API coverage (SPARK-7536) > * audit Pipeline APIs (SPARK-7535) > * graduate spark.ml from alpha > ** remove AlphaComponent annotations > ** remove mima excludes for spark.ml > h2. Algorithms and performance > *Performance* > * _List any other missing performance tests from spark-perf here_ > * LDA online/EM (SPARK-7455) > * ElasticNet for linear regression and logistic regression (SPARK-7456) > * Bernoulli naive Bayes (SPARK-7453) > * PIC (SPARK-7454) > * ALS.recommendAll (SPARK-7457) > * perf-tests in Python (SPARK-7539) > *Correctness* > * PMML > ** scoring using PMML evaluator vs. MLlib models (SPARK-7540) > * model save/load (SPARK-7541) > h2. Documentation and example code > * Create JIRAs for the user guide to each new algorithm and assign them to > the corresponding author. Link here as "requires" > * Create example code for major components > ** cross validation in python > ** pipeline with complex feature transformations (scala/java/python) > ** elastic-net (possibly with cross validation) -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org