[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify the code snippets into categories from the provided list of categories. List of categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']"}, {'role': 'user', 'content': 'Identify to which category the provided code belongs and assign the code snippet to at least 1 but up to 5 categories based on the probabilities, ignore if the probability of the category is negligible. Strictly provide your response as a list. Avoid providing any additional information, commentary, or personal opinions.\\nPython Code:def plot_decision_boundary(pred_func):\nx_min, x_max = X[:, 0].min() - .5, X[:, 0].max() + .5\ny_min, y_max = X[:, 1].min() - .5, X[:, 1].max() + .5\nh = 0.01\nxx, yy = np.meshgrid(np.arange(x_min, x_max, h), np.arange(y_min, y_max, h))\nZ = pred_func(np.c_[xx.ravel(), yy.ravel()])\nZ = Z.reshape(xx.shape)\nplt.contourf(xx, yy, Z, cmap=plt.cm.Spectral)\nplt.scatter(X[:, 0], X[:, 1], c=Y, cmap=plt.cm.Spectral)'}, {'role': 'assistant', 'content': "['result_visualization']"}]