Hi;
I am trying to classify documents.
When i try to predict (same of training set) there is only 1 and -1
predictions.
Accuracy is 0%.
Can you help me please?
val env = ExecutionEnvironment.getExecutionEnvironment
val training = Seq(
new LabeledVector(1.0, new SparseVector(10, Array(0, 2, 3), Array(1.0,
1.0, 1.0))),
new LabeledVector(1.0, new SparseVector(10, Array(0, 1, 5, 9),
Array(1.0, 1.0, 1.0, 1.0))),
new LabeledVector(0.0, new SparseVector(10, Array(0, 2), Array(0.0,
1.0))),
new LabeledVector(0.0, new SparseVector(10, Array(0), Array(0.0))),
new LabeledVector(2.0, new SparseVector(10, Array(0, 2), Array(0.0,
1.0))),
new LabeledVector(2.0, new SparseVector(10, Array(0), Array(0.0))),
new LabeledVector(1.0, new SparseVector(10, Array(0, 3), Array(1.0,
1.0))),
new LabeledVector(0.0, new SparseVector(10, Array(0, 2, 3), Array(0.0,
1.0, 1.0))),
new LabeledVector(2.0, new SparseVector(10, Array(0, 7, 9), Array(0.0,
1.0))),
new LabeledVector(2.0, new SparseVector(10, Array(2,3,4),
Array(0.0,1.0,1.0))),
new LabeledVector(2.0, new SparseVector(10, Array(0, 3), Array(1.0,
1.0))),
new LabeledVector(0.0, new SparseVector(10, Array(2, 3,9), Array(1.0,
0.0, 1.0)))
);
val trainingDS = env.fromCollection(training)
val testingDS = env.fromCollection(training)
val svm = new SVM().setBlocks(env.getParallelism)
svm.fit(trainingDS)
val predictions = svm.evaluate(testingDS.map(x => (x.vector, x.label)))
predictions.print();
Sample output:
(1.0,1.0)
(1.0,1.0)
(0.0,1.0)
(0.0,-1.0)
(2.0,1.0)
(2.0,-1.0)
(1.0,1.0)
(0.0,1.0)
(2.0,1.0)
(2.0,1.0)
(2.0,1.0)
(0.0,1.0)
