👀 Views: 80 💬 Answers: 1 📅 Created: 2025-06-05

scikit-learn gridsearchcv random-forest machine-learning Python

Hey everyone, I'm running into an issue that's driving me crazy. I've searched everywhere and can't find a clear answer. I'm running into a `ValueError` when I try to use `GridSearchCV` with a `RandomForestClassifier` in Scikit-learn version 1.0.2. The behavior message reads: `ValueError: Expected 2D array, got 1D array instead:`. I am trying to optimize the hyperparameters for my classifier, but it seems like the input data is causing issues. Here's a snippet of my code where I'm setting up `GridSearchCV`: ```python from sklearn.ensemble import RandomForestClassifier from sklearn.model_selection import GridSearchCV from sklearn.datasets import load_iris from sklearn.model_selection import train_test_split # Load dataset and split it X, y = load_iris(return_X_y=True) X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42) # Create a random forest classifier rf = RandomForestClassifier(random_state=42) # Define hyperparameter grid param_grid = { 'n_estimators': [100, 200], 'max_depth': [None, 10, 20], } # Set up GridSearchCV grid_search = GridSearchCV(estimator=rf, param_grid=param_grid, scoring='accuracy', cv=5) # Fit the model grid_search.fit(X_train, y_train) ``` I’ve double-checked the shapes of `X_train` and `y_train`, and they both seem correct: `X_train.shape` shows (120, 4) and `y_train.shape` shows (120,). I suspect the scenario could be related to how the data is being fed into the `fit` method or perhaps something I'm missing in the setup. I've also ensured that `y_train` is a 1D array as expected. Has anyone experienced a similar scenario with `GridSearchCV`? What could be causing this ValueError, and how can I resolve it? I'm working on a web app that needs to handle this.