Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Llew Mason"'
Publikováno v:
Machine Learning. 57:83-113
The architecture of Blue Martini Software's e-commerce suite has supported data collection, data transformation, and data mining since its inception. With clickstreams being collected at the application-server layer, high-level events being logged, a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0e2705923e43bc791e99082146f8e59b
https://doi.org/10.1023/b:mach.0000035473.11134.83
https://doi.org/10.1023/b:mach.0000035473.11134.83
Publikováno v:
ACM SIGKDD Explorations Newsletter. 2:86-93
We describe KDD-Cup 2000, the yearly competition in data mining. For the first time the Cup included insight problems in addition to prediction problems, thus posing new challenges in both the knowledge discovery and the evaluation criteria, and high
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b00314e45de5a84ec38e35da4cfed6f1
https://doi.org/10.1145/380995.381033
https://doi.org/10.1145/380995.381033
Publikováno v:
KDD
This study compares five well-known association rule algorithms using three real-world datasets and an artificial dataset. The experimental results confirm the performance improvements previously claimed by the authors on the artificial data, but som
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9523402abfcc690ed339563aed5347ed
https://doi.org/10.1145/502512.502572
https://doi.org/10.1145/502512.502572
Publikováno v:
ICDM
We show that the e-commerce domain can provide all the right ingredients for successful data mining and claim that it is a killer domain for data mining. We describe an integrated architecture, based on our expe-rience at Blue Martini Software, for s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1eaa2e7e53297a2a9af9ceb02839288d
http://arxiv.org/abs/cs/0007026
http://arxiv.org/abs/cs/0007026
Publikováno v:
Journal of Computer and System Sciences. (2):415-438
We derive an upper bound on the generalization error of classifiers which can be represented as thresholded convex combinations of thresholded convex combinations of functions. Such classifiers include single hidden-layer threshold networks and voted
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a8331bd22fd505d1d4c8ba254b4efe1c