Clustering in Knime

A retail company sends out a lot of promotions with different kinds of offers and discounts to customers. Each campaign is composed of several different kinds of elements: A type of campaign (often also one or several discount levels), addons, and requirements. Every campaign must have exactly one type but can have zero or more addons or requirements. Below is a typical example of a campaign: 40% on first item + free delivery if above 800 There are 7 different kinds of campaign types: check, first item, first + second item, combinations, all order, ladder, three items for the price of two. Each campaign can also contain free addons: a free or payed gift, shipping, express shipping, return. The requirements put restraints on which kind of items that will warrant discounts: items on sale, ordinary and/or reduced price, brand selection, minimum value of order, minimum number of items, time. The level of discount can differ and is also given. The company wants to be able to understand how profit and activation are affected by the combination of type, discounts, addons and requirements. Data Since this is not a predictive task, only historical orders are provided: HistoricalOrders_Profit_Activation. The full descrition is in docs file.I have done most of the work of lab i just need you to do the last six parts of the lab and also writre the report for them