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Philip Bordner
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llm4healthcare
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[0f1df3]: / AICare-baselines / configs / experiments_challenge.py

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hparams =[

    {

        'model': 'GRU',

        'dataset': 'challenge',

        'task': 'outcome',

        'epochs': 50,

        'patience': 10,

        'batch_size': 1024,

        'learning_rate': 0.001,

        'main_metric': 'auprc',

        'demo_dim': 5,

        'lab_dim': 33,

        'hidden_dim': 128,

        'output_dim': 1

    },

    {

        'model': 'Transformer',

        'dataset': 'challenge',

        'task': 'outcome',

        'epochs': 50,

        'patience': 10,

        'batch_size': 1024,

        'learning_rate': 0.001,

        'main_metric': 'auprc',

        'demo_dim': 5,

        'lab_dim': 33,

        'hidden_dim': 128,

        'output_dim': 1

    },

    {

        'model': 'MTRHN',

        'dataset': 'challenge',

        'task': 'outcome',

        'epochs': 50,

        'patience': 10,

        'batch_size': 1024,

        'learning_rate': 0.001,

        'main_metric': 'auprc',

        'demo_dim': 5,

        'lab_dim': 33,

        'hidden_dim': 128,

        'output_dim': 1

    },

    {

        'model': 'LSTM',

        'dataset': 'challenge',

        'task': 'outcome',

        'epochs': 50,

        'patience': 10,

        'batch_size': 1024,

        'learning_rate': 0.001,

        'main_metric': 'auprc',

        'demo_dim': 5,

        'lab_dim': 33,

        'hidden_dim': 128,

        'output_dim': 1

    },

    {

        'model': 'BiLSTM',

        'dataset': 'challenge',

        'task': 'outcome',

        'epochs': 50,

        'patience': 10,

        'batch_size': 1024,

        'learning_rate': 0.001,

        'main_metric': 'auprc',

        'demo_dim': 5,

        'lab_dim': 33,

        'hidden_dim': 128,

        'output_dim': 1

    },

    # {

    #     'model': 'AICare',

    #     'dataset': 'challenge',

    #     'task': 'outcome',

    #     'epochs': 50,

    #     'patience': 10,

    #     'batch_size': 1024,

    #     'learning_rate': 0.001,

    #     'main_metric': 'auprc',

    #     'demo_dim': 5,

    #     'lab_dim': 33,

    #     'hidden_dim': 128,

    #     'output_dim': 1

    # },

    {

        "model": "LR",

        "dataset": "challenge",

        "task": "outcome",

        "max_depth": 5,

        "n_estimators": 10,

        "learning_rate": 0.01,

        "batch_size": 81920,

        "main_metric": "auprc",

    },

    {

        "model": "XGBoost",

        "dataset": "challenge",

        "task": "outcome",

        "max_depth": 5,

        "n_estimators": 50,

        "learning_rate": 0.1,

        "batch_size": 81920,

        "main_metric": "auprc",

    },

    {

        "model": "DT",

        "dataset": "challenge",

        "task": "outcome",

        "max_depth": 5,

        "n_estimators": 10,

        "learning_rate": 0.01,

        "batch_size": 81920,

        "main_metric": "auprc",

    },

    {

        "model": "LightGBM",

        "dataset": "challenge",

        "task": "outcome",

        "max_depth": 5,

        "n_estimators": 50,

        "learning_rate": 0.01,

        "batch_size": 81920,

        "main_metric": "auprc",

    },

]