Commit d2204f89 authored by Jeffrey Gleason's avatar Jeffrey Gleason Committed by Sujen

Lstm pipelines

parent 30dd3585
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{"problem": "LL1_HandOutlines_problem","full_inputs": ["LL1_HandOutlines_dataset"],"train_inputs": ["LL1_HandOutlines_dataset_TRAIN"],"test_inputs": ["LL1_HandOutlines_dataset_TEST"],"score_inputs": ["LL1_HandOutlines_dataset_SCORE"]}
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{"problem": "LL1_OSULeaf_problem","full_inputs": ["LL1_OSULeaf_dataset"],"train_inputs": ["LL1_OSULeaf_dataset_TRAIN"],"test_inputs": ["LL1_OSULeaf_dataset_TEST"],"score_inputs": ["LL1_OSULeaf_dataset_SCORE"]}
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{"problem": "SEMI_1040_sylva_prior_problem","full_inputs": ["SEMI_1040_sylva_prior_dataset"],"train_inputs": ["SEMI_1040_sylva_prior_dataset_TRAIN"],"test_inputs": ["SEMI_1040_sylva_prior_dataset_TEST"],"score_inputs": ["SEMI_1040_sylva_prior_dataset_SCORE"]}
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{"problem": "LL1_Haptics_problem","full_inputs": ["LL1_Haptics_dataset"],"train_inputs": ["LL1_Haptics_dataset_TRAIN"],"test_inputs": ["LL1_Haptics_dataset_TEST"],"score_inputs": ["LL1_Haptics_dataset_SCORE"]}
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{"problem": "SEMI_1040_sylva_prior_problem","full_inputs": ["SEMI_1040_sylva_prior_dataset"],"train_inputs": ["SEMI_1040_sylva_prior_dataset_TRAIN"],"test_inputs": ["SEMI_1040_sylva_prior_dataset_TEST"],"score_inputs": ["SEMI_1040_sylva_prior_dataset_SCORE"]}
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{"problem": "SEMI_1217_click_prediction_small_problem","full_inputs": ["SEMI_1217_click_prediction_small_dataset"],"train_inputs": ["SEMI_1217_click_prediction_small_dataset_TRAIN"],"test_inputs": ["SEMI_1217_click_prediction_small_dataset_TEST"],"score_inputs": ["SEMI_1217_click_prediction_small_dataset_SCORE"]}
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{"problem": "LL1_Meat_problem","full_inputs": ["LL1_Meat_dataset"],"train_inputs": ["LL1_Meat_dataset_TRAIN"],"test_inputs": ["LL1_Meat_dataset_TEST"],"score_inputs": ["LL1_Meat_dataset_SCORE"]}
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{"problem": "LL1_Cricket_Y_problem","full_inputs": ["LL1_Cricket_Y_dataset"],"train_inputs": ["LL1_Cricket_Y_dataset_TRAIN"],"test_inputs": ["LL1_Cricket_Y_dataset_TEST"],"score_inputs": ["LL1_Cricket_Y_dataset_SCORE"]}
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{"problem": "LL1_ItalyPowerDemand_problem","full_inputs": ["LL1_ItalyPowerDemand_dataset"],"train_inputs": ["LL1_ItalyPowerDemand_dataset_TRAIN"],"test_inputs": ["LL1_ItalyPowerDemand_dataset_TEST"],"score_inputs": ["LL1_ItalyPowerDemand_dataset_SCORE"]}
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{"problem": "SEMI_1217_click_prediction_small_problem","full_inputs": ["SEMI_1217_click_prediction_small_dataset"],"train_inputs": ["SEMI_1217_click_prediction_small_dataset_TRAIN"],"test_inputs": ["SEMI_1217_click_prediction_small_dataset_TEST"],"score_inputs": ["SEMI_1217_click_prediction_small_dataset_SCORE"]}
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{"problem": "LL1_FordA_problem","full_inputs": ["LL1_FordA_dataset"],"train_inputs": ["LL1_FordA_dataset_TRAIN"],"test_inputs": ["LL1_FordA_dataset_TEST"],"score_inputs": ["LL1_FordA_dataset_SCORE"]}
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{"problem": "LL1_FISH_problem","full_inputs": ["LL1_FISH_dataset"],"train_inputs": ["LL1_FISH_dataset_TRAIN"],"test_inputs": ["LL1_FISH_dataset_TEST"],"score_inputs": ["LL1_FISH_dataset_SCORE"]}
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{"problem": "LL1_FaceFour_problem","full_inputs": ["LL1_FaceFour_dataset"],"train_inputs": ["LL1_FaceFour_dataset_TRAIN"],"test_inputs": ["LL1_FaceFour_dataset_TEST"],"score_inputs": ["LL1_FaceFour_dataset_SCORE"]}
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{"id": "ab52b9c5-5865-4e5a-8929-3d738d0f0e6c", "schema": "https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json", "created": "2019-06-15T23:40:59.041688Z", "inputs": [{"name": "inputs"}], "outputs": [{"data": "steps.1.produce", "name": "output predictions"}], "steps": [{"type": "PRIMITIVE", "primitive": {"id": "f31f8c1f-d1c5-43e5-a4b2-2ae4a761ef2e", "version": "0.2.0", "python_path": "d3m.primitives.data_transformation.denormalize.Common", "name": "Denormalize datasets", "digest": "00ae7955cc0abce2a3ddee96247209f3395009ae6553c7ce8caa577e402754db"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "inputs.0"}}, "outputs": [{"id": "produce"}]}, {"type": "PRIMITIVE", "primitive": {"id": "77bf4b92-2faa-3e38-bb7e-804131243a7f", "version": "2.0.3", "python_path": "d3m.primitives.clustering.k_means.Sloth", "name": "Sloth", "digest": "fbc8676a154fee7f8eff3e13fd8fc2cc81d621c1e927011d24e8e8371dffeed7"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.0.produce"}, "outputs": {"type": "CONTAINER", "data": "steps.0.produce"}}, "outputs": [{"id": "produce"}], "hyperparams": {"nclusters": {"type": "VALUE", "data": 2}, "long_format": {"type": "VALUE", "data": true}}}], "digest": "0dba7146bcdd9248fa3f369ad79b40b850cb7f034408841ef338df00294ec188"}
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{"problem": "SEMI_1040_sylva_prior_problem","full_inputs": ["SEMI_1040_sylva_prior_dataset"],"train_inputs": ["SEMI_1040_sylva_prior_dataset_TRAIN"],"test_inputs": ["SEMI_1040_sylva_prior_dataset_TEST"],"score_inputs": ["SEMI_1040_sylva_prior_dataset_SCORE"]}
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{"problem": "66_chlorineConcentration_problem","full_inputs": ["66_chlorineConcentration_dataset"],"train_inputs": ["66_chlorineConcentration_dataset_TRAIN"],"test_inputs": ["66_chlorineConcentration_dataset_TEST"],"score_inputs": ["66_chlorineConcentration_dataset_SCORE"]}
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{"id": "bfd65a88-b696-4d6e-a880-ec1b779511ae", "schema": "https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json", "created": "2019-06-14T00:51:50.757517Z", "inputs": [{"name": "inputs"}], "outputs": [{"data": "steps.1.produce", "name": "output predictions"}], "steps": [{"type": "PRIMITIVE", "primitive": {"id": "f31f8c1f-d1c5-43e5-a4b2-2ae4a761ef2e", "version": "0.2.0", "python_path": "d3m.primitives.data_transformation.denormalize.Common", "name": "Denormalize datasets", "digest": "00ae7955cc0abce2a3ddee96247209f3395009ae6553c7ce8caa577e402754db"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "inputs.0"}}, "outputs": [{"id": "produce"}]}, {"type": "PRIMITIVE", "primitive": {"id": "77bf4b92-2faa-3e38-bb7e-804131243a7f", "version": "2.0.3", "python_path": "d3m.primitives.clustering.k_means.Sloth", "name": "Sloth", "digest": "ed4370dc52fc0c0f824c2e1bc72ff30fd1624d4ba1d0e466518a5ef743ec29b0"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.0.produce"}, "outputs": {"type": "CONTAINER", "data": "steps.0.produce"}}, "outputs": [{"id": "produce"}], "hyperparams": {"nclusters": {"type": "VALUE", "data": 37}}}], "digest": "cf01182414958d2c2cb3588835ac89e518fbad2dc965bc8f4b9a540f4bfa14de"}
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{"problem": "LL1_Adiac_problem","full_inputs": ["LL1_Adiac_dataset"],"train_inputs": ["LL1_Adiac_dataset_TRAIN"],"test_inputs": ["LL1_Adiac_dataset_TEST"],"score_inputs": ["LL1_Adiac_dataset_SCORE"]}
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{"id": "cf801ad9-5214-4fe3-ad13-906c766b4302", "schema": "https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json", "created": "2019-06-14T00:52:37.087839Z", "inputs": [{"name": "inputs"}], "outputs": [{"data": "steps.1.produce", "name": "output predictions"}], "steps": [{"type": "PRIMITIVE", "primitive": {"id": "f31f8c1f-d1c5-43e5-a4b2-2ae4a761ef2e", "version": "0.2.0", "python_path": "d3m.primitives.data_transformation.denormalize.Common", "name": "Denormalize datasets", "digest": "00ae7955cc0abce2a3ddee96247209f3395009ae6553c7ce8caa577e402754db"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "inputs.0"}}, "outputs": [{"id": "produce"}]}, {"type": "PRIMITIVE", "primitive": {"id": "77bf4b92-2faa-3e38-bb7e-804131243a7f", "version": "2.0.3", "python_path": "d3m.primitives.clustering.k_means.Sloth", "name": "Sloth", "digest": "ed4370dc52fc0c0f824c2e1bc72ff30fd1624d4ba1d0e466518a5ef743ec29b0"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.0.produce"}, "outputs": {"type": "CONTAINER", "data": "steps.0.produce"}}, "outputs": [{"id": "produce"}], "hyperparams": {"nclusters": {"type": "VALUE", "data": 3}}}], "digest": "ca303cb78233dece19c5c42135e498948bd502409477240f0d3c0c76fea37674"}
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{"problem": "LL1_ArrowHead_problem","full_inputs": ["LL1_ArrowHead_dataset"],"train_inputs": ["LL1_ArrowHead_dataset_TRAIN"],"test_inputs": ["LL1_ArrowHead_dataset_TEST"],"score_inputs": ["LL1_ArrowHead_dataset_SCORE"]}
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{"id": "d4d236cf-a379-4346-9930-2635a6344932", "schema": "https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json", "created": "2019-06-14T02:17:52.943821Z", "inputs": [{"name": "inputs"}], "outputs": [{"data": "steps.1.produce", "name": "output predictions"}], "steps": [{"type": "PRIMITIVE", "primitive": {"id": "f31f8c1f-d1c5-43e5-a4b2-2ae4a761ef2e", "version": "0.2.0", "python_path": "d3m.primitives.data_transformation.denormalize.Common", "name": "Denormalize datasets", "digest": "00ae7955cc0abce2a3ddee96247209f3395009ae6553c7ce8caa577e402754db"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "inputs.0"}}, "outputs": [{"id": "produce"}]}, {"type": "PRIMITIVE", "primitive": {"id": "77bf4b92-2faa-3e38-bb7e-804131243a7f", "version": "2.0.3", "python_path": "d3m.primitives.clustering.k_means.Sloth", "name": "Sloth", "digest": "ed4370dc52fc0c0f824c2e1bc72ff30fd1624d4ba1d0e466518a5ef743ec29b0"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.0.produce"}, "outputs": {"type": "CONTAINER", "data": "steps.0.produce"}}, "outputs": [{"id": "produce"}], "hyperparams": {"nclusters": {"type": "VALUE", "data": 2}}}], "digest": "2469ed6c7f3497c9526f90c36f81cae1a733661b7cd0f273e57f3dee68b72b99"}
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{"problem": "LL1_ECG200_problem","full_inputs": ["LL1_ECG200_dataset"],"train_inputs": ["LL1_ECG200_dataset_TRAIN"],"test_inputs": ["LL1_ECG200_dataset_TEST"],"score_inputs": ["LL1_ECG200_dataset_SCORE"]}
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{"id": "4b0395de-9cc3-4c64-b5d1-78dc2bac904a", "schema": "https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json", "created": "2019-06-14T19:40:08.695855Z", "inputs": [{"name": "inputs"}], "outputs": [{"data": "steps.5.produce", "name": "output predictions"}], "steps": [{"type": "PRIMITIVE", "primitive": {"id": "4b42ce1e-9b98-4a25-b68e-fad13311eb65", "version": "0.3.0", "python_path": "d3m.primitives.data_transformation.dataset_to_dataframe.Common", "name": "Extract a DataFrame from a Dataset", "digest": "0d46a2c5bc374e305682dc4f1c322518c07638153a8365034a513ea46960802b"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "inputs.0"}}, "outputs": [{"id": "produce"}]}, {"type": "PRIMITIVE", "primitive": {"id": "04573880-d64f-4791-8932-52b7c3877639", "version": "3.0.2", "python_path": "d3m.primitives.feature_selection.pca_features.Pcafeatures", "name": "PCA Features", "digest": "803f20bea77432bc0b3c2a65788ff58865252104bb6883bd2e6447c9806958c2"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.0.produce"}}, "outputs": [{"id": "produce"}]}, {"type": "PRIMITIVE", "primitive": {"id": "d510cb7a-1782-4f51-b44c-58f0236e47c7", "version": "0.5.0", "python_path": "d3m.primitives.data_transformation.column_parser.DataFrameCommon", "name": "Parses strings into their types", "digest": "312cacc014497dd674e34765f6eb54430e594c591e760da0383c87844753d2ce"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.1.produce"}}, "outputs": [{"id": "produce"}]}, {"type": "PRIMITIVE", "primitive": {"id": "d016df89-de62-3c53-87ed-c06bb6a23cde", "version": "2019.4.4", "python_path": "d3m.primitives.data_cleaning.imputer.SKlearn", "name": "sklearn.impute.SimpleImputer", "digest": "9878fdeb255c5b4fb2beaf053e68b2913e3d7b1c26e40c530c1cb4fe562fde26"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.2.produce"}}, "outputs": [{"id": "produce"}], "hyperparams": {"return_result": {"type": "VALUE", "data": "replace"}, "use_semantic_types": {"type": "VALUE", "data": true}}}, {"type": "PRIMITIVE", "primitive": {"id": "1dd82833-5692-39cb-84fb-2455683075f3", "version": "2019.4.4", "python_path": "d3m.primitives.classification.random_forest.SKlearn", "name": "sklearn.ensemble.forest.RandomForestClassifier", "digest": "1e95597335ea675f941f08c916e586a414c0405a2ea0e3da0a0e3b1ee47ba761"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.3.produce"}, "outputs": {"type": "CONTAINER", "data": "steps.3.produce"}}, "outputs": [{"id": "produce"}], "hyperparams": {"add_index_columns": {"type": "VALUE", "data": true}, "use_semantic_types": {"type": "VALUE", "data": true}}}, {"type": "PRIMITIVE", "primitive": {"id": "8d38b340-f83f-4877-baaa-162f8e551736", "version": "0.3.0", "python_path": "d3m.primitives.data_transformation.construct_predictions.DataFrameCommon", "name": "Construct pipeline predictions output", "digest": "cfb2d595652c4ae0d24e67d4cb8e4916c9f3c2753eaccc2935263d054b3682fa"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.4.produce"}, "reference": {"type": "CONTAINER", "data": "steps.0.produce"}}, "outputs": [{"id": "produce"}]}], "digest": "02807fea853282db9b6f8c91f7806e3c16ae094c39b6a35a6a241c35a71c88ff"}
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{"problem": "LL0_1100_popularkids_problem","full_inputs": ["LL0_1100_popularkids_dataset"],"train_inputs": ["LL0_1100_popularkids_dataset_TRAIN"],"test_inputs": ["LL0_1100_popularkids_dataset_TEST"],"score_inputs": ["LL0_1100_popularkids_dataset_SCORE"]}
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{"id": "6b368880-850d-4db9-b6d0-a582de99f2b8", "schema": "https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json", "created": "2019-06-14T19:39:44.087747Z", "inputs": [{"name": "inputs"}], "outputs": [{"data": "steps.5.produce", "name": "output predictions"}], "steps": [{"type": "PRIMITIVE", "primitive": {"id": "4b42ce1e-9b98-4a25-b68e-fad13311eb65", "version": "0.3.0", "python_path": "d3m.primitives.data_transformation.dataset_to_dataframe.Common", "name": "Extract a DataFrame from a Dataset", "digest": "0d46a2c5bc374e305682dc4f1c322518c07638153a8365034a513ea46960802b"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "inputs.0"}}, "outputs": [{"id": "produce"}]}, {"type": "PRIMITIVE", "primitive": {"id": "04573880-d64f-4791-8932-52b7c3877639", "version": "3.0.2", "python_path": "d3m.primitives.feature_selection.pca_features.Pcafeatures", "name": "PCA Features", "digest": "803f20bea77432bc0b3c2a65788ff58865252104bb6883bd2e6447c9806958c2"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.0.produce"}}, "outputs": [{"id": "produce"}]}, {"type": "PRIMITIVE", "primitive": {"id": "d510cb7a-1782-4f51-b44c-58f0236e47c7", "version": "0.5.0", "python_path": "d3m.primitives.data_transformation.column_parser.DataFrameCommon", "name": "Parses strings into their types", "digest": "312cacc014497dd674e34765f6eb54430e594c591e760da0383c87844753d2ce"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.1.produce"}}, "outputs": [{"id": "produce"}]}, {"type": "PRIMITIVE", "primitive": {"id": "d016df89-de62-3c53-87ed-c06bb6a23cde", "version": "2019.4.4", "python_path": "d3m.primitives.data_cleaning.imputer.SKlearn", "name": "sklearn.impute.SimpleImputer", "digest": "9878fdeb255c5b4fb2beaf053e68b2913e3d7b1c26e40c530c1cb4fe562fde26"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.2.produce"}}, "outputs": [{"id": "produce"}], "hyperparams": {"return_result": {"type": "VALUE", "data": "replace"}, "use_semantic_types": {"type": "VALUE", "data": true}}}, {"type": "PRIMITIVE", "primitive": {"id": "1dd82833-5692-39cb-84fb-2455683075f3", "version": "2019.4.4", "python_path": "d3m.primitives.classification.random_forest.SKlearn", "name": "sklearn.ensemble.forest.RandomForestClassifier", "digest": "1e95597335ea675f941f08c916e586a414c0405a2ea0e3da0a0e3b1ee47ba761"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.3.produce"}, "outputs": {"type": "CONTAINER", "data": "steps.3.produce"}}, "outputs": [{"id": "produce"}], "hyperparams": {"add_index_columns": {"type": "VALUE", "data": true}, "use_semantic_types": {"type": "VALUE", "data": true}}}, {"type": "PRIMITIVE", "primitive": {"id": "8d38b340-f83f-4877-baaa-162f8e551736", "version": "0.3.0", "python_path": "d3m.primitives.data_transformation.construct_predictions.DataFrameCommon", "name": "Construct pipeline predictions output", "digest": "cfb2d595652c4ae0d24e67d4cb8e4916c9f3c2753eaccc2935263d054b3682fa"}, "arguments": {"inputs": {"type": "CONTAINER", "data": "steps.4.produce"}, "reference": {"type": "CONTAINER", "data": "steps.0.produce"}}, "outputs": [{"id": "produce"}]}], "digest": "012c7bfa586d27ef7b3a457970101ad1cf08746436487c2d2fa597aed90e6d43"}
\ No newline at end of file
{"problem": "1491_one_hundred_plants_margin_problem","full_inputs": ["1491_one_hundred_plants_margin_dataset"],"train_inputs": ["1491_one_hundred_plants_margin_dataset_TRAIN"],"test_inputs": ["1491_one_hundred_plants_margin_dataset_TEST"],"score_inputs": ["1491_one_hundred_plants_margin_dataset_SCORE"]}
\ No newline at end of file
......@@ -15,7 +15,7 @@
"installation": [
{
"type": "PIP",
"package_uri": "git+https://github.com/NewKnowledge/[email protected]e61e47271324f57f04bb00e4530a0f63aa8fe9eb#egg=PcafeaturesD3MWrapper"
"package_uri": "git+https://github.com/NewKnowledge/[email protected]4b31ed6098236ef7392768c45e4fa2f238124d3c#egg=PcafeaturesD3MWrapper"
}
],
"python_path": "d3m.primitives.feature_selection.pca_features.Pcafeatures",
......@@ -210,5 +210,5 @@
},
"structural_type": "PcafeaturesD3MWrapper.wrapper.pcafeatures",
"description": "Perform principal component analysis on all numeric data in the dataset\nand then use each original features contribution to the first principal\ncomponent as a proxy for the 'score' of that feature. Returns a dataframe\ncontaining an ordered list of all original features as well as their\ncontribution to the first principal component.\n\nAttributes\n----------\nmetadata : PrimitiveMetadata\n Primitive's metadata. Available as a class attribute.\nlogger : Logger\n Primitive's logger. Available as a class attribute.\nhyperparams : Hyperparams\n Hyperparams passed to the constructor.\nrandom_seed : int\n Random seed passed to the constructor.\ndocker_containers : Dict[str, DockerContainer]\n A dict mapping Docker image keys from primitive's metadata to (named) tuples containing\n container's address under which the container is accessible by the primitive, and a\n dict mapping exposed ports to ports on that address.\nvolumes : Dict[str, str]\n A dict mapping volume keys from primitive's metadata to file and directory paths\n where downloaded and extracted files are available to the primitive.\ntemporary_directory : str\n An absolute path to a temporary directory a primitive can use to store any files\n for the duration of the current pipeline run phase. Directory is automatically\n cleaned up after the current pipeline run phase finishes.",
"digest": "bb6d6eafb7a066bd64cf440eda072d94392e3752332b287673de2687b3b44d65"
}
\ No newline at end of file
"digest": "0922d56aa3b37da0fe5b5e1b4db57e2f2e205d87710479f5236d982a8530ba7b"
}
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{"problem": "LL1_FaceFour_problem","full_inputs": ["LL1_FaceFour_dataset"],"train_inputs": ["LL1_FaceFour_dataset_TRAIN"],"test_inputs": ["LL1_FaceFour_dataset_TEST"],"score_inputs": ["LL1_FaceFour_dataset_SCORE"]}
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