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Diffstat (limited to 'python/pyspark/ml/regression.py')
| -rw-r--r-- | python/pyspark/ml/regression.py | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/python/pyspark/ml/regression.py b/python/pyspark/ml/regression.py index 944e648ec8..a0bb8ceed8 100644 --- a/python/pyspark/ml/regression.py +++ b/python/pyspark/ml/regression.py @@ -40,7 +40,7 @@ class LinearRegression(JavaEstimator, HasFeaturesCol, HasLabelCol, HasPrediction Linear regression. The learning objective is to minimize the squared error, with regularization. - The specific squared error loss function used is: L = 1/2n ||A weights - y||^2^ + The specific squared error loss function used is: L = 1/2n ||A coefficients - y||^2^ This support multiple types of regularization: - none (a.k.a. ordinary least squares) |