5ffd5d3838
## What changes were proposed in this pull request? Made DataFrame-based API primary * Spark doc menu bar and other places now link to ml-guide.html, not mllib-guide.html * mllib-guide.html keeps RDD-specific list of features, with a link at the top redirecting people to ml-guide.html * ml-guide.html includes a "maintenance mode" announcement about the RDD-based API * **Reviewers: please check this carefully** * (minor) Titles for DF API no longer include "- spark.ml" suffix. Titles for RDD API have "- RDD-based API" suffix * Moved migration guide to ml-guide from mllib-guide * Also moved past guides from mllib-migration-guides to ml-migration-guides, with a redirect link on mllib-migration-guides * **Reviewers**: I did not change any of the content of the migration guides. Reorganized DataFrame-based guide: * ml-guide.html mimics the old mllib-guide.html page in terms of content: overview, migration guide, etc. * Moved Pipeline description into ml-pipeline.html and moved tuning into ml-tuning.html * **Reviewers**: I did not change the content of these guides, except some intro text. * Sidebar remains the same, but with pipeline and tuning sections added Other: * ml-classification-regression.html: Moved text about linear methods to new section in page ## How was this patch tested? Generated docs locally Author: Joseph K. Bradley <joseph@databricks.com> Closes #14213 from jkbradley/ml-guide-2.0.
48 lines
2.8 KiB
Markdown
48 lines
2.8 KiB
Markdown
---
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layout: global
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title: "MLlib: RDD-based API"
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displayTitle: "MLlib: RDD-based API"
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---
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This page documents sections of the MLlib guide for the RDD-based API (the `spark.mllib` package).
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Please see the [MLlib Main Guide](ml-guide.html) for the DataFrame-based API (the `spark.ml` package),
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which is now the primary API for MLlib.
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* [Data types](mllib-data-types.html)
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* [Basic statistics](mllib-statistics.html)
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* [summary statistics](mllib-statistics.html#summary-statistics)
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* [correlations](mllib-statistics.html#correlations)
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* [stratified sampling](mllib-statistics.html#stratified-sampling)
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* [hypothesis testing](mllib-statistics.html#hypothesis-testing)
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* [streaming significance testing](mllib-statistics.html#streaming-significance-testing)
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* [random data generation](mllib-statistics.html#random-data-generation)
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* [Classification and regression](mllib-classification-regression.html)
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* [linear models (SVMs, logistic regression, linear regression)](mllib-linear-methods.html)
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* [naive Bayes](mllib-naive-bayes.html)
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* [decision trees](mllib-decision-tree.html)
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* [ensembles of trees (Random Forests and Gradient-Boosted Trees)](mllib-ensembles.html)
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* [isotonic regression](mllib-isotonic-regression.html)
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* [Collaborative filtering](mllib-collaborative-filtering.html)
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* [alternating least squares (ALS)](mllib-collaborative-filtering.html#collaborative-filtering)
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* [Clustering](mllib-clustering.html)
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* [k-means](mllib-clustering.html#k-means)
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* [Gaussian mixture](mllib-clustering.html#gaussian-mixture)
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* [power iteration clustering (PIC)](mllib-clustering.html#power-iteration-clustering-pic)
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* [latent Dirichlet allocation (LDA)](mllib-clustering.html#latent-dirichlet-allocation-lda)
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* [bisecting k-means](mllib-clustering.html#bisecting-kmeans)
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* [streaming k-means](mllib-clustering.html#streaming-k-means)
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* [Dimensionality reduction](mllib-dimensionality-reduction.html)
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* [singular value decomposition (SVD)](mllib-dimensionality-reduction.html#singular-value-decomposition-svd)
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* [principal component analysis (PCA)](mllib-dimensionality-reduction.html#principal-component-analysis-pca)
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* [Feature extraction and transformation](mllib-feature-extraction.html)
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* [Frequent pattern mining](mllib-frequent-pattern-mining.html)
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* [FP-growth](mllib-frequent-pattern-mining.html#fp-growth)
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* [association rules](mllib-frequent-pattern-mining.html#association-rules)
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* [PrefixSpan](mllib-frequent-pattern-mining.html#prefix-span)
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* [Evaluation metrics](mllib-evaluation-metrics.html)
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* [PMML model export](mllib-pmml-model-export.html)
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* [Optimization (developer)](mllib-optimization.html)
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* [stochastic gradient descent](mllib-optimization.html#stochastic-gradient-descent-sgd)
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* [limited-memory BFGS (L-BFGS)](mllib-optimization.html#limited-memory-bfgs-l-bfgs)
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