Hi, I'm handling a problem as shown in the below diagram, I need to predict the required output from the user inputs as shown below. I would like to know some suggestions regarding the best Machine learning approach to be used for solving this task.
Dataset for learning:
1. Every column includes different levels of value.
2. All are categorical values.
3. This is an unsupervised dataset.(There is no fixed y variable)
1. User may change the order of giving input variables.
2. User may change the number of input columns
Eg. input= column1,column2 => output= column3, column4, column 5
input= column1,column5, column3 => output= column2, column4
NOTE: We have tried the following algorithms, but looking forward for a better approach to handle this task.
1. Aprori , Eclat, FP-Growth Algorithms
2. Multi-class multi-label classification: Binary relevance, classifier chains with Random Forest and Decision Tree