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python scripts

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Natalia Szymczyk 2023-04-21 10:34:30 +02:00
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commit 99bb6baaa8
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from sklearn.model_selection import train_test_split
from sklearn.preprocessing import MinMaxScaler
from datasets import load_dataset
dataset = load_dataset("mstz/liver")['train']
dataset = dataset.to_pandas()
train, test = train_test_split(dataset, test_size=0.2, random_state=42)
train, val = train_test_split(train, test_size=0.2, random_state=42)
numerical_features = ['age', 'total_bilirubin', 'direct_ribilubin', 'alkaline_phosphotase',
'alamine_aminotransferasi', 'aspartate_aminotransferase', 'total_proteins', 'albumin',
'albumin_to_globulin_ratio']
scaler = MinMaxScaler()
train[numerical_features] = scaler.fit_transform(train[numerical_features])
test[numerical_features] = scaler.fit_transform(test[numerical_features])
val[numerical_features] = scaler.fit_transform(val[numerical_features])
train.dropna(inplace=True)
test.dropna(inplace=True)
val.dropna(inplace=True)