I'm currently building a model to predict internet auction sale prices of products in a marketplace. There are a lot of instances where a product goes for multiple prices but it's basically the same item. I have features such as category of item (clothes, kitchen, bathroom, etc.) color, weight, height, US state the item is currently in, condition of the item (good, bad, ok), and a number of other features. I have historical data dating back five years which allows me to see how much items have gone for in the past.
There are occasions when for example a bicycle might be basically the same item but there's a price variability of 100 dollars between the two items. Time of day, month, auction length help some bit but I can't seem to account for the seemingly random way that prices go up and down. One bicycle might sell for 150 dollars and the other bicycle sells for 250 dollars.
I am using Python to make the model.