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Updating the ML Doc "Estimator, Transformer, and Param" Java example to use model.extractParamMap() instead of model.fittingParamMap(), which no longer exists.
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docs/ml-guide.md

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@@ -289,7 +289,7 @@ LogisticRegressionModel model1 = lr.fit(training);
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// we can view the parameters it used during fit().
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// This prints the parameter (name: value) pairs, where names are unique IDs for this
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// LogisticRegression instance.
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System.out.println("Model 1 was fit using parameters: " + model1.fittingParamMap());
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System.out.println("Model 1 was fit using parameters: " + model1.extractParamMap());
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// We may alternatively specify parameters using a ParamMap.
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ParamMap paramMap = new ParamMap();
@@ -305,7 +305,7 @@ ParamMap paramMapCombined = paramMap.$plus$plus(paramMap2);
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// Now learn a new model using the paramMapCombined parameters.
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// paramMapCombined overrides all parameters set earlier via lr.set* methods.
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LogisticRegressionModel model2 = lr.fit(training, paramMapCombined);
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System.out.println("Model 2 was fit using parameters: " + model2.fittingParamMap());
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System.out.println("Model 2 was fit using parameters: " + model2.extractParamMap());
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// Prepare test documents.
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List<LabeledPoint> localTest = Lists.newArrayList(

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