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author | Sean Owen <sowen@cloudera.com> | 2015-07-31 13:45:28 -0700 |
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committer | Xiangrui Meng <meng@databricks.com> | 2015-07-31 13:45:28 -0700 |
commit | 873ab0f9692d8ea6220abdb8d9200041068372a8 (patch) | |
tree | e1116f9c5a53c796943ad189be61aceca5f31653 /docs/mllib-evaluation-metrics.md | |
parent | 815c8245f47e61226a04e2e02f508457b5e9e536 (diff) | |
download | spark-873ab0f9692d8ea6220abdb8d9200041068372a8.tar.gz spark-873ab0f9692d8ea6220abdb8d9200041068372a8.tar.bz2 spark-873ab0f9692d8ea6220abdb8d9200041068372a8.zip |
[SPARK-9490] [DOCS] [MLLIB] MLlib evaluation metrics guide example python code uses deprecated print statement
Use print(x) not print x for Python 3 in eval examples
CC sethah mengxr -- just wanted to close this out before 1.5
Author: Sean Owen <sowen@cloudera.com>
Closes #7822 from srowen/SPARK-9490 and squashes the following commits:
01abeba [Sean Owen] Change "print x" to "print(x)" in the rest of the docs too
bd7f7fb [Sean Owen] Use print(x) not print x for Python 3 in eval examples
Diffstat (limited to 'docs/mllib-evaluation-metrics.md')
-rw-r--r-- | docs/mllib-evaluation-metrics.md | 66 |
1 files changed, 33 insertions, 33 deletions
diff --git a/docs/mllib-evaluation-metrics.md b/docs/mllib-evaluation-metrics.md index 4ca0bb06b2..7066d5c974 100644 --- a/docs/mllib-evaluation-metrics.md +++ b/docs/mllib-evaluation-metrics.md @@ -302,10 +302,10 @@ predictionAndLabels = test.map(lambda lp: (float(model.predict(lp.features)), lp metrics = BinaryClassificationMetrics(predictionAndLabels) # Area under precision-recall curve -print "Area under PR = %s" % metrics.areaUnderPR +print("Area under PR = %s" % metrics.areaUnderPR) # Area under ROC curve -print "Area under ROC = %s" % metrics.areaUnderROC +print("Area under ROC = %s" % metrics.areaUnderROC) {% endhighlight %} @@ -606,24 +606,24 @@ metrics = MulticlassMetrics(predictionAndLabels) precision = metrics.precision() recall = metrics.recall() f1Score = metrics.fMeasure() -print "Summary Stats" -print "Precision = %s" % precision -print "Recall = %s" % recall -print "F1 Score = %s" % f1Score +print("Summary Stats") +print("Precision = %s" % precision) +print("Recall = %s" % recall) +print("F1 Score = %s" % f1Score) # Statistics by class labels = data.map(lambda lp: lp.label).distinct().collect() for label in sorted(labels): - print "Class %s precision = %s" % (label, metrics.precision(label)) - print "Class %s recall = %s" % (label, metrics.recall(label)) - print "Class %s F1 Measure = %s" % (label, metrics.fMeasure(label, beta=1.0)) + print("Class %s precision = %s" % (label, metrics.precision(label))) + print("Class %s recall = %s" % (label, metrics.recall(label))) + print("Class %s F1 Measure = %s" % (label, metrics.fMeasure(label, beta=1.0))) # Weighted stats -print "Weighted recall = %s" % metrics.weightedRecall -print "Weighted precision = %s" % metrics.weightedPrecision -print "Weighted F(1) Score = %s" % metrics.weightedFMeasure() -print "Weighted F(0.5) Score = %s" % metrics.weightedFMeasure(beta=0.5) -print "Weighted false positive rate = %s" % metrics.weightedFalsePositiveRate +print("Weighted recall = %s" % metrics.weightedRecall) +print("Weighted precision = %s" % metrics.weightedPrecision) +print("Weighted F(1) Score = %s" % metrics.weightedFMeasure()) +print("Weighted F(0.5) Score = %s" % metrics.weightedFMeasure(beta=0.5)) +print("Weighted false positive rate = %s" % metrics.weightedFalsePositiveRate) {% endhighlight %} </div> @@ -881,28 +881,28 @@ scoreAndLabels = sc.parallelize([ metrics = MultilabelMetrics(scoreAndLabels) # Summary stats -print "Recall = %s" % metrics.recall() -print "Precision = %s" % metrics.precision() -print "F1 measure = %s" % metrics.f1Measure() -print "Accuracy = %s" % metrics.accuracy +print("Recall = %s" % metrics.recall()) +print("Precision = %s" % metrics.precision()) +print("F1 measure = %s" % metrics.f1Measure()) +print("Accuracy = %s" % metrics.accuracy) # Individual label stats labels = scoreAndLabels.flatMap(lambda x: x[1]).distinct().collect() for label in labels: - print "Class %s precision = %s" % (label, metrics.precision(label)) - print "Class %s recall = %s" % (label, metrics.recall(label)) - print "Class %s F1 Measure = %s" % (label, metrics.f1Measure(label)) + print("Class %s precision = %s" % (label, metrics.precision(label))) + print("Class %s recall = %s" % (label, metrics.recall(label))) + print("Class %s F1 Measure = %s" % (label, metrics.f1Measure(label))) # Micro stats -print "Micro precision = %s" % metrics.microPrecision -print "Micro recall = %s" % metrics.microRecall -print "Micro F1 measure = %s" % metrics.microF1Measure +print("Micro precision = %s" % metrics.microPrecision) +print("Micro recall = %s" % metrics.microRecall) +print("Micro F1 measure = %s" % metrics.microF1Measure) # Hamming loss -print "Hamming loss = %s" % metrics.hammingLoss +print("Hamming loss = %s" % metrics.hammingLoss) # Subset accuracy -print "Subset accuracy = %s" % metrics.subsetAccuracy +print("Subset accuracy = %s" % metrics.subsetAccuracy) {% endhighlight %} @@ -1283,10 +1283,10 @@ scoreAndLabels = predictions.join(ratingsTuple).map(lambda tup: tup[1]) metrics = RegressionMetrics(scoreAndLabels) # Root mean sqaured error -print "RMSE = %s" % metrics.rootMeanSquaredError +print("RMSE = %s" % metrics.rootMeanSquaredError) # R-squared -print "R-squared = %s" % metrics.r2 +print("R-squared = %s" % metrics.r2) {% endhighlight %} @@ -1479,17 +1479,17 @@ valuesAndPreds = parsedData.map(lambda p: (float(model.predict(p.features)), p.l metrics = RegressionMetrics(valuesAndPreds) # Squared Error -print "MSE = %s" % metrics.meanSquaredError -print "RMSE = %s" % metrics.rootMeanSquaredError +print("MSE = %s" % metrics.meanSquaredError) +print("RMSE = %s" % metrics.rootMeanSquaredError) # R-squared -print "R-squared = %s" % metrics.r2 +print("R-squared = %s" % metrics.r2) # Mean absolute error -print "MAE = %s" % metrics.meanAbsoluteError +print("MAE = %s" % metrics.meanAbsoluteError) # Explained variance -print "Explained variance = %s" % metrics.explainedVariance +print("Explained variance = %s" % metrics.explainedVariance) {% endhighlight %} |