diff --git a/src/python/nimbusml/examples/AveragedPerceptronBinaryClassifier.py b/src/python/nimbusml/examples/AveragedPerceptronBinaryClassifier.py index 69566dab..1e0bd727 100644 --- a/src/python/nimbusml/examples/AveragedPerceptronBinaryClassifier.py +++ b/src/python/nimbusml/examples/AveragedPerceptronBinaryClassifier.py @@ -20,7 +20,6 @@ feature=['age', 'parity', 'spontaneous'], label='case')]) # train, predict, and evaluate -# TODO: Replace with CV metrics, predictions = pipeline.fit(data).test(data, output_scores=True) # print predictions diff --git a/src/python/nimbusml/examples/FactorizationMachineBinaryClassifier.py b/src/python/nimbusml/examples/FactorizationMachineBinaryClassifier.py index 508f8a84..52dbcc6f 100644 --- a/src/python/nimbusml/examples/FactorizationMachineBinaryClassifier.py +++ b/src/python/nimbusml/examples/FactorizationMachineBinaryClassifier.py @@ -26,7 +26,6 @@ ]) # train, predict, and evaluate -# TODO: Replace with CV metrics, predictions = pipeline.fit(data).test(data, output_scores=True) # print predictions diff --git a/src/python/nimbusml/examples/FastForestBinaryClassifier.py b/src/python/nimbusml/examples/FastForestBinaryClassifier.py index aa7f34ed..1f1a5e3f 100644 --- a/src/python/nimbusml/examples/FastForestBinaryClassifier.py +++ b/src/python/nimbusml/examples/FastForestBinaryClassifier.py @@ -25,7 +25,6 @@ ]) # train, predict, and evaluate -# TODO: Replace with CV metrics, predictions = pipeline.fit(data).test(data, output_scores=True) # print predictions diff --git a/src/python/nimbusml/examples/FastLinearBinaryClassifier.py b/src/python/nimbusml/examples/FastLinearBinaryClassifier.py index fd38072a..73f72f03 100644 --- a/src/python/nimbusml/examples/FastLinearBinaryClassifier.py +++ b/src/python/nimbusml/examples/FastLinearBinaryClassifier.py @@ -23,7 +23,6 @@ ]) # train, predict, and evaluate -# TODO: Replace with CV metrics, predictions = pipeline.fit(data).test(data, output_scores=True) # print predictions diff --git a/src/python/nimbusml/examples/FastLinearClassifier.py b/src/python/nimbusml/examples/FastLinearClassifier.py index d668a49e..32d00ecd 100644 --- a/src/python/nimbusml/examples/FastLinearClassifier.py +++ b/src/python/nimbusml/examples/FastLinearClassifier.py @@ -24,7 +24,6 @@ ]) # train, predict, and evaluate -# TODO: Replace with CV metrics, predictions = pipeline.fit(data).test(data, output_scores=True) # print predictions diff --git a/src/python/nimbusml/examples/FastLinearRegressor.py b/src/python/nimbusml/examples/FastLinearRegressor.py index 4fb64001..64b97cc4 100644 --- a/src/python/nimbusml/examples/FastLinearRegressor.py +++ b/src/python/nimbusml/examples/FastLinearRegressor.py @@ -23,7 +23,6 @@ ]) # train, predict, and evaluate -# TODO: Replace with CV metrics, predictions = pipeline.fit(data).test(data, output_scores=True) # print predictions diff --git a/src/python/nimbusml/examples/FastTreesBinaryClassifier.py b/src/python/nimbusml/examples/FastTreesBinaryClassifier.py index 4d9712e1..6a3d1458 100644 --- a/src/python/nimbusml/examples/FastTreesBinaryClassifier.py +++ b/src/python/nimbusml/examples/FastTreesBinaryClassifier.py @@ -23,7 +23,6 @@ ]) # train, predict, and evaluate -# TODO: Replace with CV metrics, predictions = pipeline.fit(data).test(data, output_scores=True) # print predictions diff --git a/src/python/nimbusml/examples/FastTreesRegressor.py b/src/python/nimbusml/examples/FastTreesRegressor.py index aac8fc38..a08ac653 100644 --- a/src/python/nimbusml/examples/FastTreesRegressor.py +++ b/src/python/nimbusml/examples/FastTreesRegressor.py @@ -23,7 +23,6 @@ ]) # train, predict, and evaluate -# TODO: Replace with CV metrics, predictions = pipeline.fit(data).test(data, output_scores=True) # print predictions diff --git a/src/python/nimbusml/examples/FastTreesTweedieRegressor.py b/src/python/nimbusml/examples/FastTreesTweedieRegressor.py index f6a0bac1..008107ac 100644 --- a/src/python/nimbusml/examples/FastTreesTweedieRegressor.py +++ b/src/python/nimbusml/examples/FastTreesTweedieRegressor.py @@ -23,7 +23,6 @@ ]) # train, predict, and evaluate -# TODO: Replace with CV metrics, predictions = pipeline.fit(data).test(data, output_scores=True) # print predictions diff --git a/src/python/nimbusml/examples/GamBinaryClassifier.py b/src/python/nimbusml/examples/GamBinaryClassifier.py index 78ee1ba4..de8d049f 100644 --- a/src/python/nimbusml/examples/GamBinaryClassifier.py +++ b/src/python/nimbusml/examples/GamBinaryClassifier.py @@ -23,7 +23,6 @@ ]) # train, predict, and evaluate -# TODO: Replace with CV metrics, predictions = pipeline.fit(data).test(data, output_scores=True) # print predictions diff --git a/src/python/nimbusml/examples/GamRegressor.py b/src/python/nimbusml/examples/GamRegressor.py index c4bf43f8..82a3b70b 100644 --- a/src/python/nimbusml/examples/GamRegressor.py +++ b/src/python/nimbusml/examples/GamRegressor.py @@ -23,7 +23,6 @@ ]) # train, predict, and evaluate -# TODO: Replace with CV metrics, predictions = pipeline.fit(data).test(data, output_scores=True) # print predictions diff --git a/src/python/nimbusml/examples/KMeansPlusPlus.py b/src/python/nimbusml/examples/KMeansPlusPlus.py index fab4c2d8..673feb95 100644 --- a/src/python/nimbusml/examples/KMeansPlusPlus.py +++ b/src/python/nimbusml/examples/KMeansPlusPlus.py @@ -24,7 +24,6 @@ ]) # train, predict, and evaluate -# TODO: Replace with CV metrics, predictions = pipeline \ .fit(data) \ .test(data, 'induced', output_scores=True) diff --git a/src/python/nimbusml/examples/LightGbmBinaryClassifier.py b/src/python/nimbusml/examples/LightGbmBinaryClassifier.py index 3774c815..b4a99dda 100644 --- a/src/python/nimbusml/examples/LightGbmBinaryClassifier.py +++ b/src/python/nimbusml/examples/LightGbmBinaryClassifier.py @@ -26,7 +26,6 @@ ]) # train, predict, and evaluate -# TODO: Replace with CV metrics, predictions = pipeline.fit( data, 'case').test( data, output_scores=True) diff --git a/src/python/nimbusml/examples/LightGbmClassifier.py b/src/python/nimbusml/examples/LightGbmClassifier.py index 15179a3b..543f72ca 100644 --- a/src/python/nimbusml/examples/LightGbmClassifier.py +++ b/src/python/nimbusml/examples/LightGbmClassifier.py @@ -26,7 +26,6 @@ ]) # train, predict, and evaluate -# TODO: Replace with CV metrics, predictions = pipeline.fit(data).test(data, output_scores=True) # print predictions diff --git a/src/python/nimbusml/examples/LightGbmRanker.py b/src/python/nimbusml/examples/LightGbmRanker.py index b137ff94..7b04a87d 100644 --- a/src/python/nimbusml/examples/LightGbmRanker.py +++ b/src/python/nimbusml/examples/LightGbmRanker.py @@ -16,7 +16,6 @@ feature=['Class', 'dep_day', 'duration'], label='rank', group_id='group')]) # train, predict, and evaluate. -# TODO: Replace with CV metrics, predictions = pipeline \ .fit(data) \ .test(data, output_scores=True) diff --git a/src/python/nimbusml/examples/LightGbmRegressor.py b/src/python/nimbusml/examples/LightGbmRegressor.py index 6165f614..cac8a047 100644 --- a/src/python/nimbusml/examples/LightGbmRegressor.py +++ b/src/python/nimbusml/examples/LightGbmRegressor.py @@ -26,7 +26,6 @@ ]) # train, predict, and evaluate -# TODO: Replace with CV metrics, predictions = pipeline.fit(data).test(data, output_scores=True) # print predictions diff --git a/src/python/nimbusml/examples/LinearSvmBinaryClassifier.py b/src/python/nimbusml/examples/LinearSvmBinaryClassifier.py index 1a2d70e6..50d760ec 100644 --- a/src/python/nimbusml/examples/LinearSvmBinaryClassifier.py +++ b/src/python/nimbusml/examples/LinearSvmBinaryClassifier.py @@ -20,7 +20,6 @@ feature=['age', 'parity', 'spontaneous'], label='case')]) # train, predict, and evaluate -# TODO: Replace with CV metrics, predictions = pipeline.fit(data).test(data, output_scores=True) # print predictions diff --git a/src/python/nimbusml/examples/LogisticRegressionBinaryClassifier.py b/src/python/nimbusml/examples/LogisticRegressionBinaryClassifier.py index a99b5dc3..e9b15be8 100644 --- a/src/python/nimbusml/examples/LogisticRegressionBinaryClassifier.py +++ b/src/python/nimbusml/examples/LogisticRegressionBinaryClassifier.py @@ -24,7 +24,6 @@ ]) # train, predict, and evaluate -# TODO: Replace with CV metrics, predictions = pipeline.fit(data).test(data, output_scores=True) # print predictions diff --git a/src/python/nimbusml/examples/LogisticRegressionClassifier.py b/src/python/nimbusml/examples/LogisticRegressionClassifier.py index 232605c8..80af4ee0 100644 --- a/src/python/nimbusml/examples/LogisticRegressionClassifier.py +++ b/src/python/nimbusml/examples/LogisticRegressionClassifier.py @@ -24,7 +24,6 @@ ]) # train, predict, and evaluate -# TODO: Replace with CV metrics, predictions = pipeline.fit(data).test(data, output_scores=True) # print predictions diff --git a/src/python/nimbusml/examples/NaiveBayesClassifier.py b/src/python/nimbusml/examples/NaiveBayesClassifier.py index 04e038af..8cabd122 100644 --- a/src/python/nimbusml/examples/NaiveBayesClassifier.py +++ b/src/python/nimbusml/examples/NaiveBayesClassifier.py @@ -25,7 +25,6 @@ ]) # train, predict, and evaluate -# TODO: Replace with CV metrics, predictions = pipeline.fit(data).test(data, output_scores=True) # print predictions diff --git a/src/python/nimbusml/examples/OneVsRestClassifier.py b/src/python/nimbusml/examples/OneVsRestClassifier.py index e5c864cb..caef3cc6 100644 --- a/src/python/nimbusml/examples/OneVsRestClassifier.py +++ b/src/python/nimbusml/examples/OneVsRestClassifier.py @@ -30,7 +30,6 @@ ]) # train, predict, and evaluate -# TODO: Replace with CV metrics, predictions = pipeline.fit(data).test(data, output_scores=True) # print predictions diff --git a/src/python/nimbusml/examples/OnlineGradientDescentRegressor.py b/src/python/nimbusml/examples/OnlineGradientDescentRegressor.py index 85f6e49f..95a6f18c 100644 --- a/src/python/nimbusml/examples/OnlineGradientDescentRegressor.py +++ b/src/python/nimbusml/examples/OnlineGradientDescentRegressor.py @@ -24,7 +24,6 @@ ]) # train, predict, and evaluate -# TODO: Replace with CV metrics, predictions = pipeline.fit(data).test(data, output_scores=True) # print predictions diff --git a/src/python/nimbusml/examples/OrdinaryLeastSquaresRegressor.py b/src/python/nimbusml/examples/OrdinaryLeastSquaresRegressor.py index c394f23b..8a9feebc 100644 --- a/src/python/nimbusml/examples/OrdinaryLeastSquaresRegressor.py +++ b/src/python/nimbusml/examples/OrdinaryLeastSquaresRegressor.py @@ -24,7 +24,6 @@ ]) # train, predict, and evaluate -# TODO: Replace with CV metrics, predictions = pipeline.fit(data).test(data, output_scores=True) # print predictions diff --git a/src/python/nimbusml/examples/PcaAnomalyDetector.py b/src/python/nimbusml/examples/PcaAnomalyDetector.py index dfe50237..8e16aa91 100644 --- a/src/python/nimbusml/examples/PcaAnomalyDetector.py +++ b/src/python/nimbusml/examples/PcaAnomalyDetector.py @@ -24,7 +24,6 @@ ]) # train, predict, and evaluate -# TODO: Replace with CV metrics, predictions = pipeline.fit(data).test( data, 'case', output_scores=True) # Score diff --git a/src/python/nimbusml/examples/PoissonRegressionRegressor.py b/src/python/nimbusml/examples/PoissonRegressionRegressor.py index 5edd5d27..0e2a3653 100644 --- a/src/python/nimbusml/examples/PoissonRegressionRegressor.py +++ b/src/python/nimbusml/examples/PoissonRegressionRegressor.py @@ -24,7 +24,6 @@ ]) # train, predict, and evaluate -# TODO: Replace with CV metrics, predictions = pipeline.fit(data).test(data, output_scores=True) # print predictions diff --git a/src/python/nimbusml/examples/SgdBinaryClassifier.py b/src/python/nimbusml/examples/SgdBinaryClassifier.py index df6c7c6a..a31576f0 100644 --- a/src/python/nimbusml/examples/SgdBinaryClassifier.py +++ b/src/python/nimbusml/examples/SgdBinaryClassifier.py @@ -24,7 +24,6 @@ ]) # train, predict, and evaluate -# TODO: Replace with CV metrics, predictions = pipeline.fit(data).test(data, output_scores=True) # print predictions diff --git a/src/python/nimbusml/examples/SymSgdBinaryClassifier.py b/src/python/nimbusml/examples/SymSgdBinaryClassifier.py index 9cae2d8f..0d5c09a5 100644 --- a/src/python/nimbusml/examples/SymSgdBinaryClassifier.py +++ b/src/python/nimbusml/examples/SymSgdBinaryClassifier.py @@ -24,7 +24,6 @@ ]) # train, predict, and evaluate -# TODO: Replace with CV metrics, predictions = pipeline.fit(data).test(data, output_scores=True) # print predictions