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A Machine Learning Approach to Conjoint Analysis
Choice-based conjoint analysis builds models of consumers preferences over products with answers gathered in questionnaires. Our main goal is to bring tools from the machine learning community to solve more efficiently this problem. Thus, we propose two algorithms to estimate quickly and accurately consumer preferences.
@inproceedings{2777, title = {A Machine Learning Approach to Conjoint Analysis}, journal = {Advances in Neural Information Processing Systems}, booktitle = {Advances in Neural Information Processing Systems 17}, abstract = {Choice-based conjoint analysis builds models of consumers preferences over products with answers gathered in questionnaires. Our main goal is to bring tools from the machine learning community to solve more efficiently this problem. Thus, we propose two algorithms to estimate quickly and accurately consumer preferences.}, pages = {257-264}, editors = {Saul, L.K. , Y. Weiss, L. Bottou}, publisher = {MIT Press}, organization = {Max-Planck-Gesellschaft}, school = {Biologische Kybernetik}, address = {Cambridge, MA, USA}, month = jul, year = {2005}, slug = {2777}, author = {Chapelle, O. and Harchaoui, Z.}, month_numeric = {7} }