我有一个社交媒体帖子数据集，想预测随着时间的推移它将收到多少“赞”。

+---------+----------------+-----------+----------------+-----+-------+
| Post_id | Timestamp      | Follows   | Comments_count | ... | Likes |
+---------+----------------+-----------+----------------+-----+-------+
| 01      | 12-04-16 14:00 | 34        | 4              |     | 23    |
+---------+----------------+-----------+----------------+-----+-------+
| 01      | 12-04-16 14:35 | 35        | 7              |     | 34    |
+---------+----------------+-----------+----------------+-----+-------+
|         | ...            |           |                |     |       |
+---------+----------------+-----------+----------------+-----+-------+
| 02      | 12-04-16 14:02 | 134       | 5              |     | 36    |
+---------+----------------+-----------+----------------+-----+-------+
| 02      | 12-04-16 14:45 | 136       | 23             |     | 123   |
+---------+----------------+-----------+----------------+-----+-------+

随着时间的推移，喜欢的数量看起来像 f(x) = sqrt(x)

我的方法是为每个帖子创建一个多元多项式回归，并以某种方式对它们进行集成/平均。

这是一个好方法吗？哪种合奏技术合适？