Hi, I'm new to spark and just trying to make sense of the SVMWithSGD example.
I ran my dataset through it and build a model. When I call predict() on the
testing data (after clearThreshold()) I was expecting to get answers in the
range of 0 to 1. But they aren't, all predictions seem to be negative
numbers between -0 and -2. I guess my question is what do these predictions
mean? How are they of use? The outcome I need is a probability rather than
a binary.Here's my java code: SparkConf conf = new SparkConf()
.setAppName("name") .set("spark.cores.max", "1");
JavaSparkContext sc = new JavaSparkContext(conf); JavaRDD points =
sc.textFile(path).map(new ParsePoint()).cache(); JavaRDD training =
points.sample(false, 0.8, 0L).cache(); JavaRDD testing =
points.subtract(training); SVMModel model =
SVMWithSGD.train(training.rdd(), 100); model.clearThreshold();
for (LabeledPoint point : testing.toArray()) { Double score =
model.predict(point.features()); System.out.println("score = " +
score);//<- all these are negative numbers, seemingly between 0 and -2
}
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