Skip to content

SPARK-2293. Replace RDD.zip usage by map with predict inside. #1250

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Closed
wants to merge 1 commit into from
Closed

SPARK-2293. Replace RDD.zip usage by map with predict inside. #1250

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
18 changes: 6 additions & 12 deletions docs/mllib-naive-bayes.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -51,9 +51,8 @@ val training = splits(0)
val test = splits(1)

val model = NaiveBayes.train(training, lambda = 1.0)
val prediction = model.predict(test.map(_.features))

val predictionAndLabel = prediction.zip(test.map(_.label))
val predictionAndLabel = test.map(p => (model.predict(p.features), p.label))
val accuracy = 1.0 * predictionAndLabel.filter(x => x._1 == x._2).count() / test.count()
{% endhighlight %}
</div>
Expand All @@ -71,6 +70,7 @@ can be used for evaluation and prediction.
import org.apache.spark.api.java.JavaPairRDD;
import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.api.java.function.Function;
import org.apache.spark.api.java.function.PairFunction;
import org.apache.spark.mllib.classification.NaiveBayes;
import org.apache.spark.mllib.classification.NaiveBayesModel;
import org.apache.spark.mllib.regression.LabeledPoint;
Expand All @@ -81,18 +81,12 @@ JavaRDD<LabeledPoint> test = ... // test set

final NaiveBayesModel model = NaiveBayes.train(training.rdd(), 1.0);

JavaRDD<Double> prediction =
test.map(new Function<LabeledPoint, Double>() {
@Override public Double call(LabeledPoint p) {
return model.predict(p.features());
}
});
JavaPairRDD<Double, Double> predictionAndLabel =
prediction.zip(test.map(new Function<LabeledPoint, Double>() {
@Override public Double call(LabeledPoint p) {
return p.label();
test.mapToPair(new PairFunction<LabeledPoint, Double, Double>() {
@Override public Tuple2<Double, Double> call(LabeledPoint p) {
return new Tuple2<Double, Double>(model.predict(p.features()), p.label());
}
}));
});
double accuracy = 1.0 * predictionAndLabel.filter(new Function<Tuple2<Double, Double>, Boolean>() {
@Override public Boolean call(Tuple2<Double, Double> pl) {
return pl._1() == pl._2();
Expand Down