I have a data set of 70 stores with a sales column (ranging from 50M to 70M) and 39 other features, like age group, income categories etc. I need to find the clusters based off of these metrics.
A sample dataset will have fields like this:
Store#: 0101 Sales: 50M Customers Between 20 and 40: Low Customers Between 40 and 60: Low Customers Between 60 and 80: High Income<40: Low 40<Income<60: High 60<Income<90: Low
So you would read the dataset as follows: Store #0101 has 50M worth of sales, Low number of customers between 20 and 40, low number of customers between 40 and 60 etc.
Here are my questions:
- Does it make sense to convert Low, Medium, High to 0,0.5 and 1 respectively?
- Does sales need to get normalized between 0 and 1 ?
- Is there any other models than K-Means to address the clustering?