Automated Modeling and Nonlinear Axis Scaling

@misc{citeulike:899619, abstract = {This thesis examines nonlinear axis scaling and its impact on the modeling of inter-attribute relationships. Through automated methods, the described system identifies possible scaling methods; decides which attributes serve as inputs or outputs; and builds regression trees that quantify these relationships. While the experiments focus on the accuracy and complexity of these models, both of which one can attempt to quantitatively examine, the results also consider applicability towards...}, author = {Wu, Leejay }, citeulike-article-id = {899619}, comment = {bala}, keywords = {dimensionality\_reduction, machine\_learning}, posted-at = {2007-05-23 01:38:47}, priority = {3}, title = {Automated Modeling and Nonlinear Axis Scaling}, url = {http://citeseer.ist.psu.edu/742146.html} }

TY - GEN ID - citeulike:899619 L3 - citeulike-article-id:899619 TI - Automated Modeling and Nonlinear Axis Scaling N2 - This thesis examines nonlinear axis scaling and its impact on the modeling of inter-attribute relationships. Through automated methods, the described system identifies possible scaling methods; decides which attributes serve as inputs or outputs; and builds regression trees that quantify these relationships. While the experiments focus on the accuracy and complexity of these models, both of which one can attempt to quantitatively examine, the results also consider applicability towards... KW - dimensionality_reduction KW - machine_learning N1 - bala AU - Wu, Leejay UR - http://citeseer.ist.psu.edu/742146.html ER -