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[SW-2700] Add spline_orders to Tests Covering Parameter Propagation to H2OGAMMOJOModel #2760

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merged 1 commit into from Apr 11, 2022
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[SW-2700] Add spline_orders to Tests Covering Parameter Propagation to H2OGAMMOJOModel #2760

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1 change: 1 addition & 0 deletions ml/src/test/scala/ai/h2o/sparkling/ml/models/MOJOParameterTestSuite.scala
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Expand Up @@ -102,6 +102,7 @@ class MOJOParameterTestSuite extends FunSuite with SharedH2OTestContext with Mat
.setNumKnots(Array(5, 5))
.setBs(Array(1, 1))
.setScale(Array(.5, .5))
.setSplineOrders(Array(-1, -1))
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Just a question, are those values (-1, -1) meaningful ones?

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These values haven't been selected to improve performance algorithm, but are valid according to the tests on H2O-3 side:
https://github.com/h2oai/h2o-3/pull/6090/files#diff-4340a0b6fcce0ae9216a6d99f650d45af3f198370c43a422a9f7056707c104e1R233

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Well, I can't judge if combination of Bs, NumKnots and SplineOrders is a meaningful or not, but regarding the interface extension, this is OK (straightforward).

val mojo = algorithm.fit(dataset)

compareParameterValues(algorithm, mojo, Set("getFeaturesCols"))
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2 changes: 1 addition & 1 deletion py/tests/unit/with_runtime_sparkling/test_mojo_parameters.py
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Expand Up @@ -53,7 +53,7 @@ def testGLMParameters(prostateDataset):
def testGAMParameters(prostateDataset):
features = ['AGE', 'RACE', 'DPROS', 'DCAPS', 'PSA']
algorithm = H2OGAM(seed=1, labelCol="CAPSULE", gamCols=[["PSA"], ["AGE"]], numKnots=[5, 5], lambdaValue=[0.5],
featuresCols=features, bs=[1, 1], scale=[0.5, 0.5])
featuresCols=features, bs=[1, 1], scale=[0.5, 0.5], splineOrders=[-1, -1])
model = algorithm.fit(prostateDataset)
compareParameterValues(algorithm, model, ["getFeaturesCols"])

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