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# %%
# %matplotlib inline
import datetime
import importlib
import os
import sys

import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
import yaml
from pyprojroot import here
from sklearn import linear_model, svm, kernel_ridge, gaussian_process
from sklearn.model_selection import LeaveOneGroupOut, LeavePGroupsOut, cross_val_score, cross_validate
from sklearn.metrics import mean_squared_error, r2_score
from sklearn.impute import SimpleImputer
from sklearn.dummy import DummyRegressor
import xgboost as xg

from pathlib import Path

nb_dir = os.path.split(os.getcwd())[0]
if nb_dir not in sys.path:
    sys.path.append(nb_dir)

import machine_learning.features_sensor
import machine_learning.labels
import machine_learning.model
import machine_learning.helper



# %% tags=["active-ipynb"]
# filename = Path("E:/STRAWresults/inputData/stressfulness_event/input_appraisal_stressfulness_event_mean.csv")
# filename = Path('C:/Users/Primoz/VSCodeProjects/straw2analysis/data/stressfulness_event/input_appraisal_stressfulness_event_mean.csv')

# %%
final_scores = machine_learning.helper.run_all_regression_models(filename)

# %%
final_scores.index.name = "metric"
final_scores = final_scores.set_index(["method", final_scores.index])

# %%
final_scores.to_csv("event_stressfulness_scores.csv")