public static ArgumentEncoder newNumericEncoder(int position, String name) { ArgumentEncoder r = new ArgumentEncoder(position, name); r.encoder = new ContinuousValueEncoder(name); return r; }
@Test public void testAsString() { FeatureVectorEncoder enc = new ContinuousValueEncoder("foo"); assertEquals("foo:123", enc.asString("123")); }
@Test public void testAddToVectorUsesProductOfWeights() { WordValueEncoder wv = new StaticWordValueEncoder("word"); ContinuousValueEncoder cv = new ContinuousValueEncoder("cont"); InteractionValueEncoder enc = new InteractionValueEncoder("interactions", wv, cv); Vector v1 = new DenseVector(200); enc.addInteractionToVector("a","0.9",0.5, v1); int k = enc.getProbes(); // should set k distinct locations to 0.9*0.5 assertEquals((float) k*0.5*0.9, v1.norm(1), 0); assertEquals(0.5*0.9, v1.maxValue(), 0); }
@Test public void testAddToVector() { WordValueEncoder wv = new StaticWordValueEncoder("word"); ContinuousValueEncoder cv = new ContinuousValueEncoder("cont"); InteractionValueEncoder enc = new InteractionValueEncoder("interactions", wv, cv); Vector v1 = new DenseVector(200); enc.addInteractionToVector("a","1.0",1.0, v1); int k = enc.getProbes(); // should set k distinct locations to 1 assertEquals((float) k, v1.norm(1), 0); assertEquals(1.0, v1.maxValue(), 0); // adding same interaction again should increment weights enc.addInteractionToVector("a","1.0",1.0,v1); assertEquals((float) k*2, v1.norm(1), 0); assertEquals(2.0, v1.maxValue(), 0); Vector v2 = new DenseVector(20000); enc.addInteractionToVector("a","1.0",1.0,v2); wv.addToVector("a", v2); cv.addToVector("1.0", v2); k = enc.getProbes(); //this assumes no hash collision assertEquals((float) (k + wv.getProbes()+cv.getProbes()), v2.norm(1), 1.0e-3); }
@Test public void testAddToVector() { FeatureVectorEncoder enc = new ContinuousValueEncoder("foo"); Vector v1 = new DenseVector(20); enc.addToVector("-123", v1);