Azure ML未来预测算法

我支持客户支付每月使用的各种服务的业务。我想根据客户对各种服务的历史使用情况来使用机器学习，并预测未来的使用情况（增加或减少）。Azure ML未来预测算法

我已经使用两个类来创建一个模型，它使用历史上的月份1服务用法和月份0用法来预测增长或下降。但我想开始使用所有的历史信息不仅m-1。

我该怎么做？我可以继续添加（M-2，M-3，M-4）色谱柱吗？如果是这样的话，我会有数百个专栏。

我是机器学习的新手，我不确定哪种算法对于我正在进行的分析类型非常有用。

这里是原始表的一个例子，我有：

Customer Name | MonthName  | Service | Usage 
------------- | ---------------|---------|------ 
Customer1  | January, 2017 |Service2 |$400 
Customer1  | January, 2017 |Service1 |$300 
Customer1  | January, 2017 |Service3 |$0 
Customer1  | December, 2017 |Service2 |$600 
Customer1  | December, 2017 |Service1 |$500 
Customer1  | December, 2017 |Service3 |$700 
Customer1  | November, 2016 |Service1 |$500 
Customer1  | November, 2016 |Service2 |$50 
Customer1  | October, 2016 |Service1 |$800 
Customer2  | January, 2017 |Service2 |$400 
Customer2  | January, 2017 |Service1 |$800 
Customer2  | December, 2017 |Service2 |$600 
Customer2  | December, 2017 |Service1 |$500 
Customer2  | November, 2016 |Service1 |$500 
Customer2  | November, 2016 |Service2 |$50 
Customer2  | October, 2016 |Service1 |$800

这是我现在使用拿出2级车型见下表：

+----------------+------------------+-----------------+-----------------+-----------------+-----------+-----------+-----------+-----------+-------+--------------------+ 
| Customer Name | MonthName  | Service1 - M-1 | Service2 - M-1 | Service3 - M-1 | Usage M-1 | Service1 | Service2 | Service3 | Usage | Usage Decline Flag | 
+----------------+------------------+-----------------+-----------------+-----------------+-----------+-----------+-----------+-----------+-------+--------------------+ 
| Customer1  | October, 2016 |    0 |    0 |    0 |   0 |  800 |   |   | 800 |     0 | 
| Customer1  | November, 2016 |    800 |     |     |  800 |  500 |  50 |   | 550 |     1 | 
| Customer1  | December, 2017 |    500 |    50 |     |  550 |  500 |  600 |  700 | 1800 |     0 | 
| Customer1  | January, 2017 |    500 |    600 |    700 |  1800 |  300 |  400 |   0 | 700 |     1 | 
| Customer2  | October, 2016 |    0 |    0 |    0 |   0 |  1600 |   |   | 1600 |     0 | 
| Customer2  | November, 2016 |   1600 |     |     |  1600 |  500 |  100 |   | 600 |     1 | 
| Customer2  | December, 2017 |    500 |    100 |     |  600 |  500 |  600 |   | 1100 |     0 | 
| Customer2  | January, 2017 |    500 |    600 |     |  1100 |  800 |  400 |   | 1200 |     0 | 
+----------------+------------------+-----------------+-----------------+-----------------+-----------+-----------+-----------+-----------+-------+--------------------+

来源

2017-03-03 user2669043

这是没有本质的“时间序列”学习（所以你哈每个客户都有一系列数据，并且希望能够及时预测“下一个价值”）？ – user3658307

Azure ML未来预测算法

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