[SPARK-10068] [MLLIB] Adds links to MLlib types, algos, utilities listing

mengxr jkbradley

Author: Feynman Liang <fliang@databricks.com>

Closes #8255 from feynmanliang/SPARK-10068.
This commit is contained in:
Feynman Liang 2015-08-17 15:42:14 -07:00 committed by Xiangrui Meng
parent 772e7c18fb
commit fdaf17f63f

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@ -23,19 +23,19 @@ This lists functionality included in `spark.mllib`, the main MLlib API.
* [Data types](mllib-data-types.html)
* [Basic statistics](mllib-statistics.html)
* summary statistics
* correlations
* stratified sampling
* hypothesis testing
* random data generation
* [summary statistics](mllib-statistics.html#summary-statistics)
* [correlations](mllib-statistics.html#correlations)
* [stratified sampling](mllib-statistics.html#stratified-sampling)
* [hypothesis testing](mllib-statistics.html#hypothesis-testing)
* [random data generation](mllib-statistics.html#random-data-generation)
* [Classification and regression](mllib-classification-regression.html)
* [linear models (SVMs, logistic regression, linear regression)](mllib-linear-methods.html)
* [naive Bayes](mllib-naive-bayes.html)
* [decision trees](mllib-decision-tree.html)
* [ensembles of trees](mllib-ensembles.html) (Random Forests and Gradient-Boosted Trees)
* [ensembles of trees (Random Forests and Gradient-Boosted Trees)](mllib-ensembles.html)
* [isotonic regression](mllib-isotonic-regression.html)
* [Collaborative filtering](mllib-collaborative-filtering.html)
* alternating least squares (ALS)
* [alternating least squares (ALS)](mllib-collaborative-filtering.html#collaborative-filtering)
* [Clustering](mllib-clustering.html)
* [k-means](mllib-clustering.html#k-means)
* [Gaussian mixture](mllib-clustering.html#gaussian-mixture)
@ -43,15 +43,15 @@ This lists functionality included in `spark.mllib`, the main MLlib API.
* [latent Dirichlet allocation (LDA)](mllib-clustering.html#latent-dirichlet-allocation-lda)
* [streaming k-means](mllib-clustering.html#streaming-k-means)
* [Dimensionality reduction](mllib-dimensionality-reduction.html)
* singular value decomposition (SVD)
* principal component analysis (PCA)
* [singular value decomposition (SVD)](mllib-dimensionality-reduction.html#singular-value-decomposition-svd)
* [principal component analysis (PCA)](mllib-dimensionality-reduction.html#principal-component-analysis-pca)
* [Feature extraction and transformation](mllib-feature-extraction.html)
* [Frequent pattern mining](mllib-frequent-pattern-mining.html)
* FP-growth
* [FP-growth](mllib-frequent-pattern-mining.html#fp-growth)
* [Evaluation Metrics](mllib-evaluation-metrics.html)
* [Optimization (developer)](mllib-optimization.html)
* stochastic gradient descent
* limited-memory BFGS (L-BFGS)
* [stochastic gradient descent](mllib-optimization.html#stochastic-gradient-descent-sgd)
* [limited-memory BFGS (L-BFGS)](mllib-optimization.html#limited-memory-bfgs-l-bfgs)
* [PMML model export](mllib-pmml-model-export.html)
MLlib is under active development.