diff --git a/spark/jobs/metrics/model_quality_regression_calculator.py b/spark/jobs/metrics/model_quality_regression_calculator.py index dea82897..b15a759f 100644 --- a/spark/jobs/metrics/model_quality_regression_calculator.py +++ b/spark/jobs/metrics/model_quality_regression_calculator.py @@ -6,6 +6,7 @@ from pyspark.sql.types import ArrayType, FloatType from pyspark.ml.feature import StandardScaler, VectorAssembler, Bucketizer from pyspark.ml.stat import KolmogorovSmirnovTest +from pyspark.ml.regression import LinearRegression from models.regression_model_quality import ( RegressionMetricType, @@ -181,6 +182,29 @@ def create_histogram(dataframe: DataFrame, feature: str): res = result_df.select("value_count").rdd.flatMap(lambda x: x).collect() return Histogram(buckets=buckets_spacing, values=res) + @staticmethod + def get_regression_line(model: ModelOut, dataframe: DataFrame): + dataframe_clean = dataframe.filter( + is_not_null(model.outputs.prediction.name) & is_not_null(model.target.name) + ).select(model.outputs.prediction.name, model.target.name) + + va = VectorAssembler( + inputCols=[model.outputs.prediction.name], outputCol="features" + ) + + data_va = va.transform(dataframe_clean) + + train_data = data_va.select("features", model.target.name) + + lr = LinearRegression(labelCol=model.target.name) + + # Fit the model to the data and call this model lrModel + lr_model = lr.fit(train_data) + c = lr_model.coefficients[0] + i = lr_model.intercept + + return [[0, i], [1, c + i]] + @staticmethod def residual_metrics(model: ModelOut, dataframe: DataFrame): residual_df_norm = ModelQualityRegressionCalculator.residual_calculation( @@ -209,4 +233,7 @@ def residual_metrics(model: ModelOut, dataframe: DataFrame): "targets": residual_df_norm.select(model.target.name) .rdd.flatMap(lambda x: x) .collect(), + "regression_line": ModelQualityRegressionCalculator.get_regression_line( + model, dataframe + ), } diff --git a/spark/tests/regression_current_test.py b/spark/tests/regression_current_test.py index 250096b6..3646fbd2 100644 --- a/spark/tests/regression_current_test.py +++ b/spark/tests/regression_current_test.py @@ -34,20 +34,20 @@ def reference_bike_dataframe(spark_fixture, test_data_dir): @pytest.fixture() -def current_test_fe(spark_fixture, test_data_dir): +def current_test_abalone(spark_fixture, test_data_dir): yield ( spark_fixture.read.csv( - f"{test_data_dir}/current/regression/regression_reference_test_FE.csv", + f"{test_data_dir}/current/regression/regression_abalone_current1.csv", header=True, ) ) @pytest.fixture() -def reference_test_fe(spark_fixture, test_data_dir): +def reference_test_abalone(spark_fixture, test_data_dir): yield ( spark_fixture.read.csv( - f"{test_data_dir}/reference/regression/regression_reference_test_FE.csv", + f"{test_data_dir}/reference/regression/regression_abalone_reference.csv", header=True, ) ) @@ -95,7 +95,7 @@ def model(): @pytest.fixture() -def model_test_fe(): +def model_test_abalone(): output = OutputType( prediction=ColumnDefinition(name="prediction", type=SupportedTypes.int), prediction_proba=None, @@ -134,18 +134,18 @@ def model_test_fe(): @pytest.fixture() -def current_dataset_fe(current_test_fe, model_test_fe): +def current_dataset_abalone(current_test_abalone, model_test_abalone): yield CurrentDataset( - raw_dataframe=current_test_fe, - model=model_test_fe, + raw_dataframe=current_test_abalone, + model=model_test_abalone, ) @pytest.fixture() -def reference_dataset_fe(reference_test_fe, model_test_fe): +def reference_dataset_abalone(reference_test_abalone, model_test_abalone): yield ReferenceDataset( - raw_dataframe=reference_test_fe, - model=model_test_fe, + raw_dataframe=reference_test_abalone, + model=model_test_abalone, ) @@ -227,18 +227,20 @@ def test_model_quality(spark_fixture, current_dataset, reference_dataset): ) -def test_model_quality_test_fe(spark_fixture, current_dataset_fe, reference_dataset_fe): +def test_model_quality_abalone( + spark_fixture, current_dataset_abalone, reference_dataset_abalone +): metrics_service = CurrentMetricsRegressionService( spark_session=spark_fixture, - current=current_dataset_fe, - reference=reference_dataset_fe, + current=current_dataset_abalone, + reference=reference_dataset_abalone, ) model_quality = metrics_service.calculate_model_quality() assert not deepdiff.DeepDiff( model_quality, - res.test_model_quality_test_fe_res, + res.test_model_quality_abalone_res, ignore_order=True, ignore_type_subclasses=True, ) @@ -261,11 +263,13 @@ def test_drift_regression(spark_fixture, current_dataset, reference_dataset): ) -def test_drift_regression_chi(spark_fixture, current_dataset_fe, reference_dataset_fe): +def test_drift_regression_chi( + spark_fixture, current_dataset_abalone, reference_dataset_abalone +): metrics_service = CurrentMetricsRegressionService( spark_session=spark_fixture, - current=current_dataset_fe, - reference=reference_dataset_fe, + current=current_dataset_abalone, + reference=reference_dataset_abalone, ) drift = metrics_service.calculate_drift() diff --git a/spark/tests/regression_reference_test.py b/spark/tests/regression_reference_test.py index cf22a56a..6744b4ba 100644 --- a/spark/tests/regression_reference_test.py +++ b/spark/tests/regression_reference_test.py @@ -35,9 +35,9 @@ def reference_bike_nulls(spark_fixture, test_data_dir): @pytest.fixture() -def reference_test_fe(spark_fixture, test_data_dir): +def reference_abalone(spark_fixture, test_data_dir): yield spark_fixture.read.csv( - f"{test_data_dir}/reference/regression/regression_reference_test_FE.csv", + f"{test_data_dir}/reference/regression/regression_abalone_reference.csv", header=True, ) @@ -135,7 +135,7 @@ def reference_dataset_nulls(spark_fixture, reference_bike_nulls): @pytest.fixture() -def reference_dataset_test_fe(spark_fixture, reference_test_fe): +def reference_dataset_abalone(spark_fixture, reference_abalone): output = OutputType( prediction=ColumnDefinition(name="prediction", type=SupportedTypes.int), prediction_proba=None, @@ -173,7 +173,7 @@ def reference_dataset_test_fe(spark_fixture, reference_test_fe): ) yield ReferenceDataset( - raw_dataframe=reference_test_fe, + raw_dataframe=reference_abalone, model=model, ) @@ -192,16 +192,16 @@ def test_model_quality_metrics(reference_dataset): ) -def test_model_quality_fe(reference_dataset_test_fe): +def test_model_quality_abalone(reference_dataset_abalone): metrics_service = ReferenceMetricsRegressionService( - reference=reference_dataset_test_fe, + reference=reference_dataset_abalone, ) model_quality = metrics_service.calculate_model_quality() assert not deepdiff.DeepDiff( model_quality, - res.test_model_quality_fe_res, + res.test_model_quality_abalone_res, ignore_order=True, ignore_type_subclasses=True, ) diff --git a/spark/tests/resources/reference/regression/regression_reference_test_FE.csv b/spark/tests/resources/current/regression/regression_abalone_current1.csv similarity index 50% rename from spark/tests/resources/reference/regression/regression_reference_test_FE.csv rename to spark/tests/resources/current/regression/regression_abalone_current1.csv index 9f0fe4a1..8254a7b9 100644 --- a/spark/tests/resources/reference/regression/regression_reference_test_FE.csv +++ b/spark/tests/resources/current/regression/regression_abalone_current1.csv @@ -1,3343 +1,3760 @@ Sex,Length,Diameter,Height,Whole_weight,Shucked_weight,Viscera_weight,Shell_weight,ground_truth,prediction,pred_id,timestamp -M,0.66,0.525,0.2,1.489,0.6065,0.3795,0.421,11,11,e73e8874-9f00-4d78-ab43-9b6840172e38,2024-01-10 08:00:00 -F,0.64,0.505,0.165,1.2235,0.5215,0.2695,0.36,2,2,721e6420-6086-4444-b1be-222404bd1194,2024-01-10 08:00:02 -M,0.65,0.515,0.18,1.463,0.658,0.3135,0.4115,2,2,4b6a472e-a124-40fe-832d-71422eb47671,2024-01-10 08:00:04 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spark/tests/resources/reference/regression/regression_abalone_reference.csv diff --git a/spark/tests/results/regression_current_results.py b/spark/tests/results/regression_current_results.py index f7c46aa2..4b15d3df 100644 --- a/spark/tests/results/regression_current_results.py +++ b/spark/tests/results/regression_current_results.py @@ -701,6 +701,7 @@ 879, 1188, ], + "regression_line": [[0, -3.1084939122534867], [1, -2.245108366586348]], }, }, "grouped_metrics": { @@ -749,18 +750,18 @@ }, } -test_model_quality_test_fe_res = { +test_model_quality_abalone_res = { "global_metrics": { - "mae": 1.9473369239976062, - "mape": 32.80513741749641, - "mse": 27.478755236385403, - "rmse": 5.242018240752831, - "r2": 0.5846200997960207, - "adj_r2": 0.5834981252756619, - "variance": 66.40816713170544, + "mae": 1.9353551476456505, + "mape": 31.485240568260803, + "mse": 27.08087257249268, + "rmse": 5.203928571040602, + "r2": 0.5889298283658604, + "adj_r2": 0.5879429967988539, + "variance": 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"CHI2", + "value": 0.4877687381632486, + "has_drift": False, + }, }, { "feature_name": "pred_id", "drift_calc": { "type": "CHI2", - "value": 0.2397280792131291, + "value": 0.2828369352729322, "has_drift": False, }, }, { "feature_name": "Length", - "drift_calc": { - "type": "KS", - "value": 0.0239680774, - "has_drift": False, - }, + "drift_calc": {"type": "KS", "value": 0.025363836, "has_drift": False}, }, { "feature_name": "Diameter", - "drift_calc": { - "type": "KS", - "value": 0.0301533877, - "has_drift": False, - }, + "drift_calc": {"type": "KS", "value": 0.0323309349, "has_drift": True}, }, { "feature_name": "Height", - "drift_calc": { - "type": "KS", - "value": 0.065718922, - "has_drift": True, - }, + "drift_calc": {"type": "KS", "value": 0.0657365912, "has_drift": True}, }, { "feature_name": "Whole_weight", - "drift_calc": { - "type": "KS", - "value": 0.0023194914, - "has_drift": False, - }, + "drift_calc": {"type": "KS", "value": 0.006636604, "has_drift": False}, }, { "feature_name": "Shucked_weight", - "drift_calc": { - "type": "KS", - "value": 0.0030926552, - "has_drift": False, - }, + "drift_calc": {"type": "KS", "value": 0.0078291138, "has_drift": False}, }, { "feature_name": "Viscera_weight", - "drift_calc": { - "type": "KS", - "value": 0.0038658189, - "has_drift": False, - }, + "drift_calc": {"type": "KS", "value": 0.0088653421, "has_drift": False}, }, { "feature_name": "Shell_weight", - "drift_calc": { - "type": "KS", - "value": 0.010824293, - "has_drift": False, - }, + "drift_calc": {"type": "KS", "value": 0.0130853067, "has_drift": False}, }, ] } diff --git a/spark/tests/results/regression_reference_results.py b/spark/tests/results/regression_reference_results.py index 4f970b6a..e097eb0a 100644 --- a/spark/tests/results/regression_reference_results.py +++ b/spark/tests/results/regression_reference_results.py @@ -2236,6 +2236,7 @@ 364, 439, ], + "regression_line": [[0, -50.98458354056082], [1, -49.937933802846935]], }, } @@ -4459,6 +4460,7 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