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Table 3. Summary of the learning-based view generalization experiment. A disjoint test set was used for testing the retrieval capability.

in SHOSLIF-O: SHOSLIF for Object Recognition and Image Retrieval (Phase II)
by Daniel L. Swets, John J. Weng 1995
"... In PAGE 22: ... We used a disjoint test set for determining the accuracy of the learning-based view generalization. The results of this experiment are summarized in Table3 . Though Table 3 shows favorable results, 100% accuracy was not achieved.... ..."
Cited by 6

Table 6. Summary of the learning-based parameter generalization experiment. A disjoint test set was used for testing the retrieval capability.

in Hierarchical Discriminant Analysis for Image Retrieval
by Daniel L. Swets, Juyang Weng 1999
"... In PAGE 29: ...1 was used. Table6 shows the data pursuant to this experiment. 3.... ..."
Cited by 32

Table 7. Summary of the learning-based view generalization experiment. A disjoint test set was used for testing the retrieval capability.

in Hierarchical Discriminant Analysis for Image Retrieval
by Daniel L. Swets, Juyang Weng 1999
Cited by 32

Table 6. Summary of the learning-based parameter generalization experiment. A disjoint test set was used for testing the retrieval capability.

in Hierarchical Discriminant Analysis for Image Retrieval
by Daniel L. Swets, John (Juyang) Weng 1999
"... In PAGE 27: ...1 was used. Table6 shows the data pursuant to this experiment.... ..."
Cited by 32

Table 7. Summary of the learning-based view generalization experiment. A disjoint test set was used for testing the retrieval capability.

in Hierarchical Discriminant Analysis for Image Retrieval
by Daniel L. Swets, John (Juyang) Weng 1999
Cited by 32

Table 3. Summary of the learning-based view generalization experiment. A disjoint test set was used for testing the retrieval capability.

in A System for Combining Traditional Alphanumeric Queries with Content-Based Queries by Example in Image Databases
by Daniel L. Swets, Yogesh Pathak, John J. Weng 1996
"... In PAGE 30: ... The results of this experiment are summarized in Table 3. Though Table3 shows favorable results, 100% accuracy was not achieved. The failures occured where the test probe viewing angle did not fall between two training sample viewing angles, as shown in Figure 29.... ..."
Cited by 8

Table 6. Summary of the learning-based parameter generalization experiment. A disjoint test set was used for testing the retrieval capability.

in Hierarchical Discriminant Analysis for Image Retrieval
by Daniel L. Swets , John Weng
"... In PAGE 25: ...1 was used. Table6 shows the data pursuant to this experiment. 3.... ..."

Table 2. A summary of annotated classes in the Bio1, Bio2 and GENIA corpora. Counts are for numbers of class instances.yThe multi-celled and mono-celled organism classes are merged in Bio2.

in Ontology Express: Statistical and Non-Monotonic Learning of Domain Ontologies from Text
by unknown authors

Table 1: Correlations for cross-year generalization. Learning-based metrics are developed from NIST 2003 Chinese data. All metrics are tested on datasets from 2003 Arabic, 2002 Chinese and 2004 Chinese.

in A Re-examination of Machine Learning Approaches for Sentence-Level MT Evaluation
by unknown authors
"... In PAGE 6: ... All metrics are tested on datasets from 2003 Arabic, 2002 Chinese and 2004 Chinese. are summarized in Table1 . We see that R03 con- sistently has a better correlation rate than the other metrics.... ..."

Table 3. CPU time (in seconds) required in the ensemble learning of base SVMs

in Diversified SVM Ensembles for Large Data Sets
by Ivor W. Tsang, Andras Kocsor, Jamest. Kwok
"... In PAGE 8: ...expensive, the orthogonal CVM is generally faster than the original implemen- tation during testing. Table3 lists the CPU time needed in the ensemble learning of base SVMs. As can be seen, the proposed method is often faster than the original MMDA by one to two orders of magnitude.... ..."
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