I know my question might look odd but I just wanted to get some insights. Every prediction model will give us predictions for validation data set and it also can give/rank features based on their weight on predictions. I am looking for one step after that. Lets say we are dealing with employee resignation and we know the most important features are pay, latest promotion, job satisfaction and external job opportunities around that employees residence. Now, is there any way that we can say which of these features is the most important feature for an individual prediction? May be for one employee, Job satisfaction is the reason behind the leave but based on our feature importance, we need to focus on pay first. I just wanted to know if there is anyway that we can do some post processing on each individual predictions?