Apples-to-apples in cross-validation studies: pitfalls in classifier performance measurement
G Forman, M Scholz - Acm Sigkdd Explorations Newsletter, 2010 - dl.acm.org
Cross-validation is a mainstay for measuring performance and progress in machine
learning. There are subtle differences in how exactly to compute accuracy, F-measure and …
learning. There are subtle differences in how exactly to compute accuracy, F-measure and …
[PDF][PDF] Apples-to-Apples in Cross-Validation Studies: Pitfalls in Classifier Performance Measurement
G Forman, M Scholz - 2009 - Citeseer
Apples-to-Apples in Cross-Validation Studies: Pitfalls in Classifier Performance Measurement
Page 1 Keyword(s): Abstract: Additional publication information: Published in ACM SIGKDD …
Page 1 Keyword(s): Abstract: Additional publication information: Published in ACM SIGKDD …
[PDF][PDF] Apples-to-Apples in Cross-Validation Studies: Pitfalls in Classifier Performance Measurement
G Forman, M Scholz - dcc.fc.up.pt
Cross-validation is a mainstay for measuring performance and progress in machine
learning. There are subtle differences in how exactly to compute accuracy, F-measure and …
learning. There are subtle differences in how exactly to compute accuracy, F-measure and …
Apples-to-apples in cross-validation studies
G Forman, M Scholz - ACM SIGKDD Explorations Newsletter, 2010 - cir.nii.ac.jp
抄録< jats: p> Cross-validation is a mainstay for measuring performance and progress in
machine learning. There are subtle differences in how exactly to compute accuracy, F …
machine learning. There are subtle differences in how exactly to compute accuracy, F …
[PDF][PDF] Apples-to-Apples in Cross-Validation Studies: Pitfalls in Classifier Performance Measurement
G Forman, M Scholz - kdd.org
Cross-validation is a mainstay for measuring performance and progress in machine
learning. There are subtle differences in how exactly to compute accuracy, F-measure and …
learning. There are subtle differences in how exactly to compute accuracy, F-measure and …
[PDF][PDF] Apples-to-Apples in Cross-Validation Studies: Pitfalls in Classifier Performance Measurement
G Forman, M Scholz - 2009 - shiftleft.com
Apples-to-Apples in Cross-Validation Studies: Pitfalls in Classifier Performance Measurement
Page 1 Keyword(s): Abstract: Additional publication information: Published in ACM SIGKDD …
Page 1 Keyword(s): Abstract: Additional publication information: Published in ACM SIGKDD …
[PDF][PDF] Apples-to-Apples in Cross-Validation Studies: Pitfalls in Classifier Performance Measurement
G Forman, M Scholz - 2009 - researchgate.net
Apples-to-Apples in Cross-Validation Studies: Pitfalls in Classifier Performance Measurement
Page 1 Keyword(s): Abstract: Additional publication information: Published in ACM SIGKDD …
Page 1 Keyword(s): Abstract: Additional publication information: Published in ACM SIGKDD …
[PDF][PDF] Apples-to-Apples in Cross-Validation Studies: Pitfalls in Classifier Performance Measurement
G Forman, M Scholz - kdd.org
Cross-validation is a mainstay for measuring performance and progress in machine
learning. There are subtle differences in how exactly to compute accuracy, F-measure and …
learning. There are subtle differences in how exactly to compute accuracy, F-measure and …
[PDF][PDF] Apples-to-Apples in Cross-Validation Studies: Pitfalls in Classifier Performance Measurement
G Forman, M Scholz - Citeseer
Cross-validation is a mainstay for measuring performance and progress in machine
learning. There are subtle differences in how exactly to compute accuracy, F-measure and …
learning. There are subtle differences in how exactly to compute accuracy, F-measure and …
[PDF][PDF] Apples-to-Apples in Cross-Validation Studies: Pitfalls in Classifier Performance Measurement
G Forman, M Scholz - dcc.fc.up.pt
Cross-validation is a mainstay for measuring performance and progress in machine
learning. There are subtle differences in how exactly to compute accuracy, F-measure and …
learning. There are subtle differences in how exactly to compute accuracy, F-measure and …