def testRegression(self): target_column = target_column_lib.regression_target() with ops.Graph().as_default(), session.Session() as sess: prediction = constant_op.constant([[1.], [1.], [3.]]) labels = constant_op.constant([[0.], [1.], [1.]]) self.assertAlmostEqual( 5. / 3, sess.run(target_column.loss(prediction, labels, {})))
def testRegressionWithWeights(self): target_column = target_column_lib.regression_target( weight_column_name="label_weight") with ops.Graph().as_default(), session.Session() as sess: features = {"label_weight": constant_op.constant([[2.], [5.], [0.]])} prediction = constant_op.constant([[1.], [1.], [3.]]) labels = constant_op.constant([[0.], [1.], [1.]]) self.assertAlmostEqual( 2. / 7, sess.run(target_column.loss(prediction, labels, features)), places=3) self.assertAlmostEqual( 2. / 3, sess.run(target_column.training_loss(prediction, labels, features)), places=3)
def testRegressionWithWeights(self): target_column = target_column_lib.regression_target( weight_column_name="label_weight") with ops.Graph().as_default(), session.Session() as sess: features = { "label_weight": constant_op.constant([[2.], [5.], [0.]]) } prediction = constant_op.constant([[1.], [1.], [3.]]) labels = constant_op.constant([[0.], [1.], [1.]]) self.assertAlmostEqual( 2. / 7, sess.run(target_column.loss(prediction, labels, features)), places=3) self.assertAlmostEqual(2. / 3, sess.run( target_column.training_loss( prediction, labels, features)), places=3)