TypeError: StratifiedKFold.split() missing 1 required positional argument: 'y'

[Programmer-RD-AI]

When attempting to run the AutoML fit method with custom StratifiedKFold cross-validation, an error occurs in the FLAML library. The error message indicates that the StratifiedKFold.split() method is missing a required positional argument: 'y'.

Code:

from flaml import AutoML
from sklearn.datasets import load_breast_cancer
from sklearn.model_selection import train_test_split, StratifiedKFold

# Load the dataset
data = load_breast_cancer()
X = data.data
y = data.target

# Split the dataset into training and testing sets
X_train, X_test, y_train, y_test = train_test_split(
    X, y, test_size=0.2, random_state=42
)

# Initialize the AutoML object
automl = AutoML()

# Define custom cross-validation split
cv = StratifiedKFold(n_splits=5, shuffle=True, random_state=42)

# Define the settings for the AutoML run
settings = {
    "time_budget": 60 * 60 * 8,  # 8 hours
    "metric": "accuracy",
    "task": "classification",
    "estimator_list": ["lgbm"],  # LightGBM
    "eval_method": "cv",  # Cross-validation
    "ensemble": True,
    "n_splits": 5,  # Number of cross-validation splits
    "split_type": cv,  # Custom split type
}

# Run the AutoML fit method
automl.fit(X_train, y_train, **settings)

Error Message:

TypeError: StratifiedKFold.split() missing 1 required positional argument: 'y'