Search Result "Multiple regression analysis"
Regression and Correlation
Ebook: Introductory Statistical Procedures with SPSS
Volume: 1 Year: 2022
Author(s): Hassan S. Bakouch
Doi: 10.2174/9789815039023122010008
Linear Regression and Logistic Regression
Ebook: Introduction to Machine Learning with Python
Volume: 1 Year: 2023
Author(s):
Doi: 10.2174/9789815124422123010005
Regression: Prediction
Ebook: Machine Learning and Its Application: A Quick Guide for Beginners
Volume: 1 Year: 2021
Author(s): Indranath Chatterjee
Doi: 10.2174/9781681089409121010007
Regression and Relapse
Ebook: Histopathological Diagnosis of Leprosy
Volume: 1 Year: 2021
Author(s): Cleverson Teixeira Soares
Doi: 10.2174/9781681087993121010011
An Enhanced Multiple Linear Regression Model for Seasonal Rainfall Prediction
Journal: International Journal of Sensors, Wireless Communications and Control
Volume: 10 Issue: 4 Year: 2020 Page: 473-483
Author(s): Pundra Chandra Shaker Reddy,Alladi Sureshbabu
Normalization of cDNA Microarray Data Using Wavelet Regressions
Journal: Combinatorial Chemistry & High Throughput Screening
Volume: 7 Issue: 8 Year: 2004 Page: 783-791
Author(s): Ju Wang, Jennie Z. Ma, Ming D. Li
Stepwise Regression Analysis of the Determinants of Blood Tacrolimus Concentrations in Chinese Patients with Liver Transplant
Journal: Medicinal Chemistry
Volume: 5 Issue: 3 Year: 2009 Page: 301-304
Author(s): Z. Jin, W. x. Zhang, B. Chen, A. W. Mao, W. M. Cai
QSAR of Antitrypanosomal Activities of Polyphenols and their Analogues Using Multiple Linear Regression and Artificial Neural Networks
Journal: Combinatorial Chemistry & High Throughput Screening
Volume: 17 Issue: 8 Year: 2014 Page: 709-717
Author(s): Vesna Rastija,Vijay H. Masand
Direct Evidence on the Immune-Mediated Spontaneous Regression of Human Cancer: An Incentive for Pharmaceutical Companies to Develop a Novel Anti-Cancer Vaccine
Journal: Current Pharmaceutical Design
Volume: 11 Issue: 2 Year: 2005 Page: 3531-3543
Author(s): F. Saleh, I. Klepacek, G. Ibrahim, H. Dashti, S. Asfar, A. Behbehani, H. Al-Sayer, A. Dashti
Comparative Studies on FDM based AM Process Using Regression Analysis and ANFIS Model
Ebook: Advances in Additive Manufacturing Processes
Volume: 1 Year: 2021
Author(s): P. Thejasree,J.S. Binoj,D. Giridhar,T.T.M. Kannan,D. Arulkirubakaran,D. Palanisamy,N. Manikandan,Ramesh Raju
Doi: 10.2174/9789815036336121010015