Pages that link to "Item:Q2629697"
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The following pages link to Advanced conjoint analysis using feature selection via support vector machines (Q2629697):
Displaying 11 items.
- Likelihood estimation of consumer preferences in choice-based conjoint analysis (Q297313) (← links)
- A hybrid conjoint model for price-demand estimation (Q1263499) (← links)
- Using factor analysis to identify consumer preferences for the protection of a natural area in Portugal (Q1598783) (← links)
- Feature selection with partition differentiation entropy for large-scale data sets (Q1750551) (← links)
- A decision analytic approach to predicting quality of life for lung transplant recipients: a hybrid genetic algorithms-based methodology (Q1754129) (← links)
- Evaluating and selecting features via information theoretic lower bounds of feature inner correlations for high-dimensional data (Q2029330) (← links)
- Learning context-dependent choice functions (Q2069057) (← links)
- Preference estimation under bounded rationality: identification of attribute non-attendance in stated-choice data using a support vector machines approach (Q2171627) (← links)
- Using hierarchical Bayes draws for improving shares of choice predictions in conjoint simulations: a study based on conjoint choice data (Q2242265) (← links)
- Estimation methods for choice-based conjoint analysis of consumer preferences (Q2275638) (← links)
- Predicting and optimizing marketing performance in dynamic markets (Q6556794) (← links)
