weight.highestValue: Calculates weights relative to the highest sum relative to...

In avilesd/productConfig: Tools to analyze behavioral patterns from Product Configurators

Description

Awards higher weights to those attirbutes which consistently showed higher values, measured against the highest posssible. Secondary function used for main function weight.highAndStandard.

Usage

weight.highestValue(dataset, userid = NULL, attr = NULL, rounds = "all",
  cost_ids = NULL)

Arguments

dataset	data.frame with the user generated data from a product configurator. See decisionMatrix for specifications of the dataset.
userid	a vector of integers that gives the information of which users the matrix should be calculated. Vectorised.
attr	attributes IDs, vector of integer numbers corresponding to the attributes you desire to use; attr are assumed to be 1-indexed. This function will calculate with all attributes and do the subsetting a posteriori. If you want to get the weights for only two attributes you will have to first use decisionMatrix and then pass it on to normalize.sum and entropy.
rounds	integer vector or text option. Which steps of the configuration process should be taken into account? Defaults are "all" in order to have more data to calculate with. If "first" or "last" are entered there will be only one rounds to gather data from, consequently all attribtues will have the same weight.
cost_ids	argument used to convert selected cost attributes into benefit attributes. Integer vector. This functions uses an alternative normalizing method normalize.highestValue that does not produce negative values.

Value

a list of weight vector(s)

avilesd/productConfig documentation built on May 11, 2019, 4:08 p.m.