I am a newbie in data mining world. I have a general question. I have a data set which has 10 independent variables and one target variable named as category which has 9 values like: 1, 2, 3, 4, 5, 6, 7, 8, 9. the 10 independent variables have different kind of range of values. some of them have values between 0 - 5000, some have big range like 5,000,000 - 100,000,000 etc.
Moreover there is no specific relation (linear etc.) existing between target and independent variables.
I am basically trying to predict the target variable category by using all of these independent variables.
Can someone suggest what should be my approach? I am very confused. Should I use regression models, decision trees or cluster analysis?