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TABLE V POLYNOMIAL CLASSIFIER RESULTS

in Occupant Classification using Range Images

by U Rangarao Devarakota, Student Member, Marta Castillo-franco, Romuald Ginhoux, Bruno Mirbach, Bjorn Ottersten 2005

Cited by 1

Table 7. Accuracy on the Pima set using Polynomial classifier.

in Mutual Information in Learning Feature Transformations

by Kari Torkkola, William M. Campbell 2000

"... In PAGE 7: ... Polynomial clas- sifier retained the same ranking orders between projection methods, and it appears to excel with low-dimensional fea- ture fectors. This is most pronounced in the results with the Pima set ( Table7 ), where only one feature produces high- est accuracies. However, LVQ excels in higher dimensions... ..."

Cited by 38

Table 7. Accuracy on the Pima set using Polynomial classifier.

in Mutual Information in Learning Feature Transformations

by Kari Torkkola, William M. Campbell 2000

Cited by 38

TABLE VII POLYNOMIAL CLASSIFIER PERFORMANCE USING PCA FEATURES

in Occupant Classification using Range Images

by U Rangarao Devarakota, Student Member, Marta Castillo-franco, Romuald Ginhoux, Bruno Mirbach, Bjorn Ottersten 2005

Cited by 1

Table 3: Speaker verification results on the YOHO database using polynomial classifiers. Polynomial EER EER Number of

in Support Vector Machines for Speaker Verification and Identification

by Vincent Wan, William M. Campbell 2000

"... In PAGE 9: ...peakers yields an average EER of 0.13% on the seen imposters and 0.32% on the unseen imposters for the 10th order normalised polynomial kernel. To put these figures into perspective the results obtained by the polynomial clas- sifiers method is shown in Table3 (which includes results of further experiments not in [3]). It can be seen that the performance of SVMs is close to but not quite as good as the polynomial classifiers technique.... ..."

Cited by 19