60 lines
1.5 KiB
Python
60 lines
1.5 KiB
Python
# ---
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# jupyter:
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# jupytext:
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# text_representation:
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# extension: .py
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# format_name: percent
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# format_version: '1.3'
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# jupytext_version: 1.13.0
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# kernelspec:
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# display_name: Python 3.10.8 ('straw2analysis')
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# language: python
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# name: python3
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# ---
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# %%
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# %matplotlib inline
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import datetime
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import importlib
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import os
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import sys
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import numpy as np
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import matplotlib.pyplot as plt
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import pandas as pd
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import seaborn as sns
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import yaml
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from pyprojroot import here
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from sklearn import linear_model, svm, kernel_ridge, gaussian_process
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from sklearn.model_selection import LeaveOneGroupOut, LeavePGroupsOut, cross_val_score, cross_validate
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from sklearn.metrics import mean_squared_error, r2_score
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from sklearn.impute import SimpleImputer
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from sklearn.dummy import DummyRegressor
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import xgboost as xg
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from pathlib import Path
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nb_dir = os.path.split(os.getcwd())[0]
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if nb_dir not in sys.path:
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sys.path.append(nb_dir)
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import machine_learning.features_sensor
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import machine_learning.labels
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import machine_learning.model
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import machine_learning.helper
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# %% tags=["active-ipynb"]
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# filename = Path("E:/STRAWresults/inputData/stressfulness_event/input_appraisal_stressfulness_event_mean.csv")
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# %%
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final_scores = machine_learning.helper.run_all_regression_models(filename)
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# %%
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final_scores.index.name = "metric"
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final_scores = final_scores.set_index(["method", final_scores.index])
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# %%
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final_scores.to_csv("event_stressfulness_scores.csv")
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