[{'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:#       .\nfrom sklearn.ensemble import RandomForestClassifier\n\ndef predict_windspeed(data):\n    \n    #  0    .\n    dataWind0 = data.loc[data[\'windspeed\'] == 0]\n    dataWindNot0 = data.loc[data[\'windspeed\'] != 0]\n    \n    #    .\n    wCol = ["season", "weather", "humidity", "month", "temp", "year", "atemp"]\n\n    #  0     .\n    dataWindNot0["windspeed"] = dataWindNot0["windspeed"].astype("str")\n\n    #   .\n    rfModel_wind = RandomForestClassifier()\n\n    # wCol      .\n    rfModel_wind.fit(dataWindNot0[wCol], dataWindNot0["windspeed"])\n\n    #     0     .\n    wind0Values = rfModel_wind.predict(X = dataWind0[wCol])\n\n    #       \n    #        .\n    predictWind0 = dataWind0\n    predictWindNot0 = dataWindNot0\n\n    #  0       .\n    predictWind0["windspeed"] = wind0Values\n\n    # dataWindNot0 0         .\n    data = predictWindNot0.append(predictWind0)\n\n    #   float  .\n    data["windspeed"] = data["windspeed"].astype("float")\n\n    data.reset_index(inplace=True)\n    data.drop(\'index\', inplace=True, axis=1)\n    \n    return data\''}, {'role': 'assistant', 'content': "['modelling']"}]