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diff --git a/docs/ml-advanced.md b/docs/ml-advanced.md index f5804fdeee..12a03d3c91 100644 --- a/docs/ml-advanced.md +++ b/docs/ml-advanced.md @@ -49,7 +49,7 @@ MLlib L-BFGS solver calls the corresponding implementation in [breeze](https://g ## Normal equation solver for weighted least squares -MLlib implements normal equation solver for [weighted least squares](https://en.wikipedia.org/wiki/Least_squares#Weighted_least_squares) by [WeightedLeastSquares](https://github.com/apache/spark/blob/master/mllib/src/main/scala/org/apache/spark/ml/optim/WeightedLeastSquares.scala). +MLlib implements normal equation solver for [weighted least squares](https://en.wikipedia.org/wiki/Least_squares#Weighted_least_squares) by [WeightedLeastSquares]({{site.SPARK_GITHUB_URL}}/blob/v{{site.SPARK_VERSION_SHORT}}/mllib/src/main/scala/org/apache/spark/ml/optim/WeightedLeastSquares.scala). Given $n$ weighted observations $(w_i, a_i, b_i)$: @@ -73,7 +73,7 @@ In order to make the normal equation approach efficient, WeightedLeastSquares re ## Iteratively reweighted least squares (IRLS) -MLlib implements [iteratively reweighted least squares (IRLS)](https://en.wikipedia.org/wiki/Iteratively_reweighted_least_squares) by [IterativelyReweightedLeastSquares](https://github.com/apache/spark/blob/master/mllib/src/main/scala/org/apache/spark/ml/optim/IterativelyReweightedLeastSquares.scala). +MLlib implements [iteratively reweighted least squares (IRLS)](https://en.wikipedia.org/wiki/Iteratively_reweighted_least_squares) by [IterativelyReweightedLeastSquares]({{site.SPARK_GITHUB_URL}}/blob/v{{site.SPARK_VERSION_SHORT}}/mllib/src/main/scala/org/apache/spark/ml/optim/IterativelyReweightedLeastSquares.scala). It can be used to find the maximum likelihood estimates of a generalized linear model (GLM), find M-estimator in robust regression and other optimization problems. Refer to [Iteratively Reweighted Least Squares for Maximum Likelihood Estimation, and some Robust and Resistant Alternatives](http://www.jstor.org/stable/2345503) for more information. |