Machine Learning - How to predict set of fixed fields based on past features I have quite a large dataset (> 100k rows), which contains information for logistical shipments. (export shipments)

The dataset looks like this:

|shipper|consignee                    |origin|destination                                  |
|-------|-----------------------------|------|---------------------------------------------|
|6409292|288882                       |USSFO |CNPVG                                        |
|6409292|288882                       |USSFO |CNPVG                                        |
|6409292|182724                       |USSFO |HKHKG                                        |
|6409292|182724                       |USSFO |HKHKG                                        |
|8201922|948292                       |USSFO |FRCDG                                        |
|8201922|948292                       |USSFO |FRCDG                                        |
|8201922|948292                       |USSFO |FRNIC                                        |
|8201922|291222                       |USEWR |AEDXB                                        |


So what we have here is a list of past shipments. It shows the relationship between shipper and consignee, and from where the shipment was from and where it was sent to.

Based on this past data, I wish to be able to predict when a new shipment is added by looking at the consignee code and origin.

Example

Take below new booking as an example:

|shipper|consignee                    |origin|destination                                  |
|-------|-----------------------------|------|---------------------------------------------|
|1234567|948292                       |USMOB |?                                            |


How can I train a model to predict the destination? And what is this area in ML referred to?
It's a supervised classification problem: you're trying to predict the destination (class) based on some categorical features (input columns). I would suggest starting with some simple algorithms such as decision trees or Naive Bayes.

However I'm guessing that logistical shipments can evolve over time: maybe a shipper business grows with country X but decreases with country Y, etc. If this is relevant, it might make sense to look into more advanced methods which could take the chronological evolution into account (time series).