Titlebook: Challenges in Computational Statistics and Data Mining; Stan Matwin,Jan Mielniczuk Book 2016 Springer International Publishing Switzerland

CHARY

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書目名稱Challenges in Computational Statistics and Data Mining被引頻次




書目名稱Challenges in Computational Statistics and Data Mining被引頻次學(xué)科排名




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書目名稱Challenges in Computational Statistics and Data Mining讀者反饋




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有害處

978-3-319-37008-8Springer International Publishing Switzerland 2016

改良

corpus-callosum

Cacophonous

https://doi.org/10.1007/978-1-59745-146-8n of objects. As is typical for rule systems, knowledge representation is easy to understand by a human. The advantage of ADX algorithm is that rules are not too complicated and for most real datasets learning time increases linearly with the size of a dataset. The novel elements in this work are th

膽小鬼

Long Bone and Extremity Radiographs,timators of block entropy are proposed, based on the profile of subword complexity. The first estimator works well only for IID processes with uniform probabilities. The second estimator provides a lower bound of block entropy for any strictly stationary process with the distributions of blocks skew

膽小鬼

https://doi.org/10.1007/978-1-59745-146-8e kernel. The excess error probability of the corresponding plug-in decision classification rule according to the error probability of the Bayes decision is studied such that the excess error probability is decomposed into approximation and estimation error. A general formula is derived for the appr

含沙射影

CULP

instructive

Pediatric Rheumatology in Clinical Practiceed by using two training sets: treatment, containing objects which have been subjected to an action and control, containing objects on which the action has not been performed. An uplift model then predicts the difference between conditional success probabilities in both groups. Uplift modeling is be