问题描述
我想创建一个程序，根据之前的查询和建议的相应建议，确定哪个选项最适合某个查询。基本上，训练系统以了解哪个建议最适合一个问题。
例如：
在这种情况下，患者输入预约号码以查看特定病房的医生。以前的数据如下：
预约编号：257 Ward指示：28
预约号码：352 Ward指示：10
预约号码：546 Ward Directed到：35
预约号码：234 Ward指示：28
正如您所注意到的，200-300范围内的约会号码已被引导至Ward 28.此后，系统将知道此范围应指向病房28.
由于这是我现在所处的分析阶段，我应该用什么最有效的方法来开发这个系统？机器学习？统计？
I want to create a program that decides which option best suits a certain query based on previous queries and their respective suggestions proposed. Basically, 'training' the system to have an idea which suggestion most suits a question.
Example:
In this scenario patients input a Appointment number to see a doctor in a specific ward. Previous data is as follows:
Appointment Number: 257 Ward Directed to: 28
Appointment Number: 352 Ward Directed to: 10
Appointment Number: 546 Ward Directed to: 35
Appointment Number: 234 Ward Directed to: 28
As you can notice, the appointment numbers within the 200-300 range have been directed to the Ward 28. Here onward, the system will know that this range should be directed to the ward 28.
Since this is the analysis stage I'm in right now, What most effective method should I use to develop this system? Machine Learning? Statistics?
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