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main.py
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main.py
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# Importing all dependencies
from sklearn.linear_model import LogisticRegression
from dataclasses_json import dataclass_json
from dataclasses import dataclass
from src.data.make_dataset import process_dataset
from src.data.split_dataset import split_dataset
from src.models.train_model import fit_model
@dataclass_json
@dataclass
class Hyperparameters(object):
filepath: str = "data/raw.csv"
test_size: float = 0.3
random_state: int = 6
hp = Hyperparameters()
def run_wf(filepath: str, test_size: float, random_state: int) -> LogisticRegression:
df = process_dataset(filepath)
X_train, X_test, y_train, y_test = split_dataset(df, test_size=test_size, random_state=random_state)
return fit_model(X_train=X_train, y_train=y_train)
if __name__=="__main__":
run_wf(filepath=hp.filepath, test_size=hp.test_size, random_state=hp.random_state)