Improving underrepresented minority student persistence in STEM
…, CG Gutiérrez, S Hurtado, GH John… - CBE—Life Sciences …, 2016 - Am Soc Cell Biol
Members of the Joint Working Group on Improving Underrepresented Minorities (URMs)
Persistence in Science, Technology, Engineering, and Mathematics (STEM)—convened by the …
Persistence in Science, Technology, Engineering, and Mathematics (STEM)—convened by the …
Wrappers for feature subset selection
… John [46] shows similar examples where adding relevant or irrelevant features to the
credit-approval and Pima diabetes datasets degrades the performance of C4.5. Aha [ l] noted that “…
credit-approval and Pima diabetes datasets degrades the performance of C4.5. Aha [ l] noted that “…
Estimating continuous distributions in Bayesian classifiers
When modeling a probability distribution with a Bayesian network, we are faced with the
problem of how to handle continuous variables. Most previous work has either solved the …
problem of how to handle continuous variables. Most previous work has either solved the …
Irrelevant features and the subset selection problem
… Since Relief randomly samples instances and their neighbors from the 126 John, Kohavi, …
filter, and observed that while it removes 128 John, Kohavi, and Pfleger some features, it does …
filter, and observed that while it removes 128 John, Kohavi, and Pfleger some features, it does …
[PDF][PDF] Robust Decision Trees: Removing Outliers from Databases.
GH John - KDD, 1995 - cdn.aaai.org
Finding and removing outliers is an important problem in data mining. Errors in large
databases can be extremely common, so an important property of a data mining algorithm is …
databases can be extremely common, so an important property of a data mining algorithm is …
Automatic parameter selection by minimizing estimated error
We address the problem of finding the parameter settings that will result in optimal performance
of a given learning algorithm using a particular dataset as training data. We describe a “…
of a given learning algorithm using a particular dataset as training data. We describe a “…
[PDF][PDF] Static Versus Dynamic Sampling for Data Mining.
As data warehouses grow to the point where one hundred gigabytes is considered small,
the computational efficiency of data-mining algorithms on large databases becomes …
the computational efficiency of data-mining algorithms on large databases becomes …
The wrapper approach
… Kohavi and John (1997) discuss early experiments with Relief and the variant we used,
Relieved-F. Relief searches for all the relevant features (both weak and strong). …
Relieved-F. Relief searches for all the relevant features (both weak and strong). …
[BOOK][B] Enhancements to the data mining process
GH John - 1997 - search.proquest.com
INFORMATION TO USERS Page 1 INFORMATION TO USERS This manuscript has been
reproduced from the microfilm master. UMI films the text directly from the original or copy …
reproduced from the microfilm master. UMI films the text directly from the original or copy …
High temperature gate control of quantum well spin memory
OZ Karimov, GH John, RT Harley, WH Lau, ME Flatté, M. Henini, and R. Airey