[{'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:from sklearn.ensemble import RandomForestClassifier\n# RandomForest   .\ndef predict_windspeed(data):\n    dataWind0 = data.loc[data["windspeed"] == 0]\n    dataWindNot0 = data.loc[data["windspeed"] != 0]\n    #   0    .\n    wcol = ["season", "weather", "humidity", "day", "temp", "atemp"]\n    #    .\n    dataWindNot0["windspeed"] = dataWindNot0["windspeed"].astype("str")\n    #  0   string .\n    rf_wind = RandomForestClassifier()\n    rf_wind.fit(dataWindNot0[wcol], dataWindNot0["windspeed"])\n    wind0 = rf_wind.predict(X=dataWind0[wcol])\n    #   wcol  0   .\n    \n    predictWind0 = dataWind0\n    predictWindNot0 = dataWindNot0\n    #     .\n    predictWind0["windspeed"] = wind0\n    #  .\n    data = predictWindNot0.append(predictWind0)\n    # 0    .\n    data["windspeed"] = data["windspeed"].astype("float")\n    #    float  .\n    data.reset_index(inplace = True)\n    data.drop("index", inplace = True, axis = 1)\n    \n    return data\n    \''}, {'role': 'assistant', 'content': "['modelling']"}]