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Each of the saved set of data was analysed for the existence of contradictory data in a selected object, selected attributes and associated values using ConTra.
See Appendix "Attribute selection based on the information gain method" for information on the numbers of selected attributes and the attributes with highest information gain value.
A summary of selected attributes appears in Table 1.
Table 6 Relative importance of selected attributes R.I.
At least one of the selected attributes has a statistically significant impact on the estimated utility.
Then, the selected attributes are the ones with the score higher than a threshold.
Inferred uses a latent class model to classify respondents depending on the estimated probability that respondents ignore selected attributes.
The number of selected attributes for JM1 is increased by one compared to the best first as well.
The performance of a classification problem depends on the relevance of the selected attributes with regard to its class.
Specifically, the likelihood ratio test rejects the null hypothesis that none of the selected attributes contribute to the derived utility.
Next, the consumer is invited to declare the weights of the selected attributes through pairwise comparisons (Fig. 5 - screen 2).
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