Commit 2e0ab48d authored by Mitar's avatar Mitar

Merge branch 'var_update_annotation' into 'master'

Var update annotation

See merge request !45
parents 5fd60c0a 83864f87
Pipeline #98463858 passed with stages
in 185 minutes and 36 seconds
......@@ -24,7 +24,7 @@
},
{
"type": "PIP",
"package_uri": "git+https://github.com/NewKnowledge/TimeSeries-D3M-Wrappers.git@19f439c7f3816a7a7941dc5023c99ea0427ab392#egg=TimeSeriesD3MWrappers"
"package_uri": "git+https://github.com/NewKnowledge/TimeSeries-D3M-Wrappers.git@953c1cd6e13eb9e4695e8fa4f4b0e89eff9d3fa4#egg=TimeSeriesD3MWrappers"
}
],
"python_path": "d3m.primitives.time_series_classification.convolutional_neural_net.LSTM_FCN",
......@@ -300,5 +300,5 @@
},
"structural_type": "TimeSeriesD3MWrappers.primitives.classification_lstm.LSTM_FCN",
"description": "Primitive that applies a LSTM FCN (LSTM fully convolutional network) for time\nseries classification. The implementation is based off this paper:\nhttps://ieeexplore.ieee.org/document/8141873 and this base library:\nhttps://github.com/NewKnowledge/LSTM-FCN.\n\nTraining inputs: 1) Feature dataframe, 2) Label dataframe\nOutputs: Dataframe with predictions\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": "0647bcee7a868e0f13a5b9e379eb525bc36693c8b9c22b1fd0f524eba5e8705b"
"digest": "d78a43004fd3ba831240df1a5f06634590763fcd50e11a42b531c68a626d35bc"
}
......@@ -23,7 +23,7 @@
},
{
"type": "PIP",
"package_uri": "git+https://github.com/NewKnowledge/TimeSeries-D3M-Wrappers.git@19f439c7f3816a7a7941dc5023c99ea0427ab392#egg=TimeSeriesD3MWrappers"
"package_uri": "git+https://github.com/NewKnowledge/TimeSeries-D3M-Wrappers.git@953c1cd6e13eb9e4695e8fa4f4b0e89eff9d3fa4#egg=TimeSeriesD3MWrappers"
}
],
"python_path": "d3m.primitives.time_series_classification.k_neighbors.Kanine",
......@@ -216,5 +216,5 @@
},
"structural_type": "TimeSeriesD3MWrappers.primitives.classification_knn.Kanine",
"description": "Primitive that applies the k nearest neighbor classification algorithm to time series data.\nThe tslearn KNeighborsTimeSeriesClassifier implementation is wrapped.\n\nTraining inputs: 1) Feature dataframe, 2) Label dataframe\nOutputs: Dataframe with predictions\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": "33c3260ca646e83d122577cc0aae86c8e583fc1593dde5be3ae14fab394c1a5a"
"digest": "4fe79abff94684da792c5195d2b999286576ada2958f2021c124262377a80691"
}
......@@ -23,7 +23,7 @@
},
{
"type": "PIP",
"package_uri": "git+https://github.com/NewKnowledge/TimeSeries-D3M-Wrappers.git@19f439c7f3816a7a7941dc5023c99ea0427ab392#egg=TimeSeriesD3MWrappers"
"package_uri": "git+https://github.com/NewKnowledge/TimeSeries-D3M-Wrappers.git@953c1cd6e13eb9e4695e8fa4f4b0e89eff9d3fa4#egg=TimeSeriesD3MWrappers"
}
],
"python_path": "d3m.primitives.time_series_forecasting.convolutional_neural_net.DeepAR",
......@@ -333,5 +333,5 @@
},
"structural_type": "TimeSeriesD3MWrappers.primitives.forecasting_deepar.DeepAR",
"description": "Primitive that applies a deep autoregressive forecasting algorithm for time series\nprediction. The implementation is based off of this paper: https://arxiv.org/pdf/1704.04110.pdf\nand is implemented in AWS's Sagemaker interface.\n\nTraining inputs: 1) Feature dataframe, 2) Target dataframe\nOutputs: Dataframe with predictions for specific time series at specific future time instances\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": "ebfce510acf74319f595d5322be1523a534c583d199649b71e5e20b709150f70"
"digest": "34bcad5856cd4cd1de34b7ca879544edad089570ef36dced4e4fb56991e969c0"
}
......@@ -20,7 +20,7 @@
},
{
"type": "PIP",
"package_uri": "git+https://github.com/NewKnowledge/TimeSeries-D3M-Wrappers.git@19f439c7f3816a7a7941dc5023c99ea0427ab392#egg=TimeSeriesD3MWrappers"
"package_uri": "git+https://github.com/NewKnowledge/TimeSeries-D3M-Wrappers.git@953c1cd6e13eb9e4695e8fa4f4b0e89eff9d3fa4#egg=TimeSeriesD3MWrappers"
}
],
"python_path": "d3m.primitives.time_series_forecasting.vector_autoregression.VAR",
......@@ -209,5 +209,5 @@
},
"structural_type": "TimeSeriesD3MWrappers.primitives.forecasting_var.VAR",
"description": "Primitive that applies a VAR multivariate forecasting model to time series data. The VAR\nimplementation comes from the statsmodels library.\n\nTraining inputs: D3M dataset with multivariate time series (potentially structured according to\n hierarchical indices) and a time series index column.\nOutputs: D3M dataset with predicted observations for a length of 'n_periods' at a certain 'interval'\n into the future\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": "4adca512c8409856305cc1c3f6f6d82b7d9a656a55ded30884e98f926ea45fb5"
"digest": "1b7c81243e1ed70bd4b025b521e58c6cabc28f1c27dda491e240004a29068dab"
}
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