33 lines
1.1 KiB
Python
33 lines
1.1 KiB
Python
import numpy as np
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import yaml
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from sklearn import linear_model
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from machine_learning.features_sensor import SensorFeatures
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from machine_learning.labels import Labels
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from machine_learning.model import ModelValidation
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if __name__ == "__main__":
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with open("./config/prox_comm_PANAS_features.yaml", "r") as file:
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sensor_features_params = yaml.safe_load(file)
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sensor_features = SensorFeatures(**sensor_features_params)
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sensor_features.set_sensor_data()
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sensor_features.calculate_features()
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with open("./config/prox_comm_PANAS_labels.yaml", "r") as file:
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labels_params = yaml.safe_load(file)
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labels = Labels(**labels_params)
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labels.set_labels()
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labels.aggregate_labels()
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model_validation = ModelValidation(
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sensor_features.get_features("all", "all"),
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labels.get_aggregated_labels(),
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group_variable="participant_id",
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cv_name="loso",
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)
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model_validation.model = linear_model.LinearRegression()
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model_validation.set_cv_method()
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model_loso_r2 = model_validation.cross_validate()
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print(model_loso_r2)
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print(np.mean(model_loso_r2))
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