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https://issues.apache.org/jira/browse/SPARK-7674?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14596672#comment-14596672
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Joseph K. Bradley commented on SPARK-7674:
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I created initial subtasks for LinearRegression. However, if someone wants to
work on another model type, we can create analogous JIRAs for those. Some
high-priority models include:
* Linear regression
* Logistic regression
* Decision tree
* K-Means clustering
* Random Forest
* Gradient-Boosted Trees
> R-like stats for ML models
> --------------------------
>
> Key: SPARK-7674
> URL: https://issues.apache.org/jira/browse/SPARK-7674
> Project: Spark
> Issue Type: New Feature
> Components: ML
> Reporter: Joseph K. Bradley
> Assignee: Joseph K. Bradley
> Priority: Critical
>
> This is an umbrella JIRA for supporting ML model summaries and statistics,
> following the example of R's summary() and plot() functions.
> [Design
> doc|https://docs.google.com/document/d/1oswC_Neqlqn5ElPwodlDY4IkSaHAi0Bx6Guo_LvhHK8/edit?usp=sharing]
> From the design doc:
> {quote}
> R and its well-established packages provide extensive functionality for
> inspecting a model and its results. This inspection is critical to
> interpreting, debugging and improving models.
> R is arguably a gold standard for a statistics/ML library, so this doc
> largely attempts to imitate it. The challenge we face is supporting similar
> functionality, but on big (distributed) data. Data size makes both efficient
> computation and meaningful displays/summaries difficult.
> R model and result summaries generally take 2 forms:
> * summary(model): Display text with information about the model and results
> on data
> * plot(model): Display plots about the model and results
> We aim to provide both of these types of information. Visualization for the
> plottable results will not be supported in MLlib itself, but we can provide
> results in a form which can be plotted easily with other tools.
> {quote}
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