Metrics

From
Predictive Modelling of Benign and Malignant Tumors Using Binary Logistic, Support Vector Machine and Extreme Gradient Boosting Models by Peter Gachoki, Moses Mburu and Moses Muraya American Journal of Applied Mathematics and Statistics. 2019, 7(6), 196-204 doi:10.12691/ajams-7-6-2
Views
12215
Html 11912
Abstract 303
27 November 2019 (publication date) through 27 November 2022 *
5.89 % of article views led to PDF downloads *
*Although we update our data on a daily basis, there may be a 48-hour delay before the most recent numbers are available.
Downloads: 10377
PDF720
Epub818
XML513
PPT5219
Figures2968
Tables139
Export: 2322
RIS640
BibTex902
Endnote780
RIS, BibTex, EndNote allows users to search, retrieve and store citations from bibliographic databases such as ABI Inform, the Web of Science, Anthropological Literature, the MLA bibliography, or the catalogs of individual libraries.
Area Chart Example: If your want to see the details of daily statistics for this article, please click here to login our Manuscript Tracking System.
Citations
0
Found additional citations for the article? Please contact us at submission@sciepub.com.
Shares & bookmarks
Facebook0
Twitter0
LinkedIn0
Google +0
Found additional shares or bookmarks for the article? Please contact us at submission@sciepub.com