One of the client requirements that we have is to find out if the vehicle or accessory configuration being done for the current year ( a large set of attributes ) is wrong based on previous year configurations.
All of the attributes are textual in nature ( vehicle type information, vehicle color , specific vehicle parameters etc) . Can you please help suggest whether ML would help solve this.
Basically the ML output should prompt the user for any anomalies in the configuration being done.
All the required data can be imported as a textual file for the yeara analyzed