diff options
Diffstat (limited to 'python')
| -rw-r--r-- | python/pyspark/ml/classification.py | 2 | ||||
| -rw-r--r-- | python/pyspark/ml/regression.py | 9 | ||||
| -rw-r--r-- | python/pyspark/ml/tuning.py | 2 | ||||
| -rw-r--r-- | python/pyspark/ml/wrapper.py | 2 |
4 files changed, 13 insertions, 2 deletions
diff --git a/python/pyspark/ml/classification.py b/python/pyspark/ml/classification.py index d98919b3c6..e64c7a392b 100644 --- a/python/pyspark/ml/classification.py +++ b/python/pyspark/ml/classification.py @@ -291,7 +291,7 @@ class LogisticRegressionSummary(JavaCallable): @since("2.0.0") def probabilityCol(self): """ - Field in "predictions" which gives the calibrated probability + Field in "predictions" which gives the probability of each class as a vector. """ return self._call_java("probabilityCol") diff --git a/python/pyspark/ml/regression.py b/python/pyspark/ml/regression.py index f6c5d130dd..1c18df3b27 100644 --- a/python/pyspark/ml/regression.py +++ b/python/pyspark/ml/regression.py @@ -331,6 +331,9 @@ class LinearRegressionSummary(JavaCallable): Standard error of estimated coefficients and intercept. This value is only available when using the "normal" solver. + If :py:attr:`LinearRegression.fitIntercept` is set to True, + then the last element returned corresponds to the intercept. + .. seealso:: :py:attr:`LinearRegression.solver` """ return self._call_java("coefficientStandardErrors") @@ -342,6 +345,9 @@ class LinearRegressionSummary(JavaCallable): T-statistic of estimated coefficients and intercept. This value is only available when using the "normal" solver. + If :py:attr:`LinearRegression.fitIntercept` is set to True, + then the last element returned corresponds to the intercept. + .. seealso:: :py:attr:`LinearRegression.solver` """ return self._call_java("tValues") @@ -353,6 +359,9 @@ class LinearRegressionSummary(JavaCallable): Two-sided p-value of estimated coefficients and intercept. This value is only available when using the "normal" solver. + If :py:attr:`LinearRegression.fitIntercept` is set to True, + then the last element returned corresponds to the intercept. + .. seealso:: :py:attr:`LinearRegression.solver` """ return self._call_java("pValues") diff --git a/python/pyspark/ml/tuning.py b/python/pyspark/ml/tuning.py index da00f317b3..ea8c61b7ef 100644 --- a/python/pyspark/ml/tuning.py +++ b/python/pyspark/ml/tuning.py @@ -588,6 +588,8 @@ class TrainValidationSplit(Estimator, ValidatorParams, MLReadable, MLWritable): class TrainValidationSplitModel(Model, ValidatorParams, MLReadable, MLWritable): """ Model from train validation split. + + .. versionadded:: 2.0.0 """ def __init__(self, bestModel): diff --git a/python/pyspark/ml/wrapper.py b/python/pyspark/ml/wrapper.py index a2cf2296fb..bbeb6cfe6f 100644 --- a/python/pyspark/ml/wrapper.py +++ b/python/pyspark/ml/wrapper.py @@ -249,7 +249,7 @@ class JavaModel(Model, JavaCallable, JavaTransformer): """ Initialize this instance with a Java model object. Subclasses should call this constructor, initialize params, - and then call _transformer_params_from_java. + and then call _transfer_params_from_java. This instance can be instantiated without specifying java_model, it will be assigned after that, but this scenario only used by |