Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Sanizah Ahmad"'
Autor:
Vanessa Enjop, Rosanita Adnan, Nursuriati Jamil, Sanizah Ahmad, Zarina Zainol, Siti Arpah Ahmad
Publikováno v:
Malaysian Journal of Computing, Vol 7, Iss 2, Pp 1236-1249 (2022)
There are a lot of sentiment resources for English, however, there are limited resources in a resource-poor language like the Malay language. One approach to improving sentiment analysis is to translate the focus-language text to a resource-rich lang
Externí odkaz:
https://doaj.org/article/0c5d59f556d64b1489e28d82bf4298fe
Publikováno v:
Proceedings of the Third International Conference on Computing, Mathematics and Statistics (iCMS2017) ISBN: 9789811372780
In logistic regression, the parameters are commonly estimated by using maximum likelihood estimator (MLE). However, MLE is easily affected when outliers appear in the data. The objective of this study is to compare the performance between the MLE and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ec4d5815a7faeba091cd47247ff87b07
https://doi.org/10.1007/978-981-13-7279-7_52
https://doi.org/10.1007/978-981-13-7279-7_52
Publikováno v:
Proceedings of the Third International Conference on Computing, Mathematics and Statistics (iCMS2017) ISBN: 9789811372780
Regression models using count data have a wide range of applications in engineering, econometrics, medicine and social sciences. Poisson regression models are widely used in the analysis and prediction of counts on potential independent variables. Ho
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7417f6e302dac6e8cd41d8992b328921
https://doi.org/10.1007/978-981-13-7279-7_28
https://doi.org/10.1007/978-981-13-7279-7_28
Autor:
Nur Aufa Mazni Ishak, Sanizah Ahmad
Publikováno v:
Regional Conference on Science, Technology and Social Sciences (RCSTSS 2016) ISBN: 9789811300738
Normally distributed data are needed in many statistical analyses including multiple regression (MR). When data is not normally distributed, remedial actions in making the data normal are necessary. In this study, the violation of this assumption is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b51590243b507d133315eae89ee6bcba
https://doi.org/10.1007/978-981-13-0074-5_102
https://doi.org/10.1007/978-981-13-0074-5_102
Autor:
Nur Aufa Mazni Ishak, Sanizah Ahmad
Publikováno v:
Regional Conference on Science, Technology and Social Sciences (RCSTSS 2016) ISBN: 9789811300738
Many real data do not conform to the assumption of homoscedasticity. In multiple regressions, the violation of the homoscedasticity assumption can be a complicating factor in estimating parameters, hypothesis testing and model selection. In this stud
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::874f1bd242bd6ce04d97c150a0378fa1
https://doi.org/10.1007/978-981-13-0074-5_103
https://doi.org/10.1007/978-981-13-0074-5_103
Publikováno v:
AIP Conference Proceedings.
In regression analysis, missing covariate data has been a common problem. Many researchers use ad hoc methods to overcome this problem due to the ease of implementation. However, these methods require assumptions about the data that rarely hold in pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f9bf0cefd1865bdf5857197319509129
https://doi.org/10.1063/1.4995930
https://doi.org/10.1063/1.4995930
Publikováno v:
AIP Conference Proceedings.
Measuring students’ ability and performance are important in assessing how well students have learned and mastered the statistical courses. Any improvement in learning will depend on the student’s approaches to learning, which are relevant to som
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b52f60ae95b5b7673f5ad3c9ad869ba9
https://doi.org/10.1063/1.4981988
https://doi.org/10.1063/1.4981988
Publikováno v:
Journal of Physics: Conference Series. 1366:012113
Common problems found in multiple linear regression models are the existence of multicollinearity and outliers. These obstacles usually produce undesirable effects on least squares estimators. Ridge regression estimator is suggested in handling sever
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c1032c2a5707924c26eac9107b710fd6
https://doi.org/10.1088/1742-6596/1366/1/012113
https://doi.org/10.1088/1742-6596/1366/1/012113
Publikováno v:
Journal of Modern Applied Statistical Methods. 9:502-511
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::93b9daa0fc4e1ff68aedb927dc039c5c
https://doi.org/10.22237/jmasm/1288585020
https://doi.org/10.22237/jmasm/1288585020
The refinement of partial robust M-regression model using winsorized mean and Hampel weight function
Publikováno v:
AIP Conference Proceedings.
Partial Robust M-Regression (PRM) is a robust Partial Least Squares (PLS) method using M-estimator, with multivariate L1 median and a monotonous weight function, known as Fair function in its algorithm. In many studies, the use of re-descending weigh
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9bc88954c97c47f96a73581534c14d48
https://doi.org/10.1063/1.4907441
https://doi.org/10.1063/1.4907441