diff options
Diffstat (limited to 'docs/ml-guide.md')
| -rw-r--r-- | docs/ml-guide.md | 8 |
1 files changed, 4 insertions, 4 deletions
diff --git a/docs/ml-guide.md b/docs/ml-guide.md index c5f50ed799..4eb622d4b9 100644 --- a/docs/ml-guide.md +++ b/docs/ml-guide.md @@ -207,7 +207,7 @@ val model1 = lr.fit(training.toDF) // we can view the parameters it used during fit(). // This prints the parameter (name: value) pairs, where names are unique IDs for this // LogisticRegression instance. -println("Model 1 was fit using parameters: " + model1.fittingParamMap) +println("Model 1 was fit using parameters: " + model1.parent.extractParamMap) // We may alternatively specify parameters using a ParamMap, // which supports several methods for specifying parameters. @@ -222,7 +222,7 @@ val paramMapCombined = paramMap ++ paramMap2 // Now learn a new model using the paramMapCombined parameters. // paramMapCombined overrides all parameters set earlier via lr.set* methods. val model2 = lr.fit(training.toDF, paramMapCombined) -println("Model 2 was fit using parameters: " + model2.fittingParamMap) +println("Model 2 was fit using parameters: " + model2.parent.extractParamMap) // Prepare test data. val test = sc.parallelize(Seq( @@ -289,7 +289,7 @@ LogisticRegressionModel model1 = lr.fit(training); // we can view the parameters it used during fit(). // This prints the parameter (name: value) pairs, where names are unique IDs for this // LogisticRegression instance. -System.out.println("Model 1 was fit using parameters: " + model1.fittingParamMap()); +System.out.println("Model 1 was fit using parameters: " + model1.parent().extractParamMap()); // We may alternatively specify parameters using a ParamMap. ParamMap paramMap = new ParamMap(); @@ -305,7 +305,7 @@ ParamMap paramMapCombined = paramMap.$plus$plus(paramMap2); // Now learn a new model using the paramMapCombined parameters. // paramMapCombined overrides all parameters set earlier via lr.set* methods. LogisticRegressionModel model2 = lr.fit(training, paramMapCombined); -System.out.println("Model 2 was fit using parameters: " + model2.fittingParamMap()); +System.out.println("Model 2 was fit using parameters: " + model2.parent().extractParamMap()); // Prepare test documents. List<LabeledPoint> localTest = Lists.newArrayList( |