lujiaying

from autogluon.tabular import TabularPredictor, TabularDataset


if __name__ == '__main__':
    path_prefix = 'https://autogluon.s3.amazonaws.com/datasets/CoverTypeMulticlassClassification/'
    path_train = path_prefix + 'train_data.csv'
    path_test = path_prefix + 'test_data.csv'

    label = 'Cover_Type'
    sample = 20000  # Number of rows to use to train

lujiaying

讨论结果

2016.05.11讨论

假设：

1. 不考虑无交互的行为（即用户突然听新歌的行为）
2. 不考虑用户规模的问题
3. 若考虑实际用户规模大于user表规模，则做二级的回归：第一级首先对用户-歌曲的每日听歌量进行回归，第二级是根据user表中的听歌量预测总用户的听歌量

lujiaying

// Use Gists to store code you would like to remember later on
console.log(window); // log the "window" object to the console