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Diffstat (limited to 'docs/ml-classification-regression.md')
| -rw-r--r-- | docs/ml-classification-regression.md | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/docs/ml-classification-regression.md b/docs/ml-classification-regression.md index 1aacc3e054..43cc79b9c0 100644 --- a/docs/ml-classification-regression.md +++ b/docs/ml-classification-regression.md @@ -984,7 +984,7 @@ Random forests combine many decision trees in order to reduce the risk of overfi The `spark.ml` implementation supports random forests for binary and multiclass classification and for regression, using both continuous and categorical features. -For more information on the algorithm itself, please see the [`spark.mllib` documentation on random forests](mllib-ensembles.html). +For more information on the algorithm itself, please see the [`spark.mllib` documentation on random forests](mllib-ensembles.html#random-forests). ### Inputs and Outputs @@ -1065,7 +1065,7 @@ GBTs iteratively train decision trees in order to minimize a loss function. The `spark.ml` implementation supports GBTs for binary classification and for regression, using both continuous and categorical features. -For more information on the algorithm itself, please see the [`spark.mllib` documentation on GBTs](mllib-ensembles.html). +For more information on the algorithm itself, please see the [`spark.mllib` documentation on GBTs](mllib-ensembles.html#gradient-boosted-trees-gbts). ### Inputs and Outputs |