References

3.4 Evaluating Forecast Accuracy | Forecasting: Principles and Practice (2nd Ed). n.d.

Bellon-Maurel, Véronique, Elvira Fernandez-Ahumada, Bernard Palagos, Jean-Michel Roger, and Alex McBratney. 2010. “Critical Review of Chemometric Indicators Commonly Used for Assessing the Quality of the Prediction of Soil Attributes by NIR Spectroscopy.” TrAC Trends in Analytical Chemistry 29 (9): 1073–81. https://doi.org/10.1016/j.trac.2010.05.006.

Bohachevsky, Ihor O., Mark E. Johnson, and Myron L. Stein. 1986. “Generalized Simulated Annealing for Function Optimization.” Technometrics 28 (3): 209–17. https://doi.org/10.1080/00401706.1986.10488128.

Bolstad, Benjamin Milo. 2004. Low-Level Analysis of High-density Oligonucleotide Array Data: Background, Normalization and Summarization. University of California, Berkeley.

Booth, Gordon D., George E. P. Box, William G. Hunter, and J. Stuart Hunter. 1979. “Statistics for Experimenters: An Introduction to Design, Data Analysis, and Model Building.” Journal of the American Statistical Association 74 (367): 731. https://doi.org/10.2307/2287009.

Couch, Simon P., Andrew P. Bray, Chester Ismay, Evgeni Chasnovski, Benjamin S. Baumer, and Mine Çetinkaya-Rundel. 2021. “Infer: An r Package for Tidyverse-Friendly Statistical Inference” 6: 3661. https://doi.org/10.21105/joss.03661.

Craig-Schapiro, Rebecca, Max Kuhn, Chengjie Xiong, Eve H. Pickering, Jingxia Liu, Thomas P. Misko, Richard J. Perrin, et al. 2011. “Multiplexed Immunoassay Panel Identifies Novel CSF Biomarkers for Alzheimer’s Disease Diagnosis and Prognosis.” Edited by Ashley I. Bush. PLoS ONE 6 (4): e18850. https://doi.org/10.1371/journal.pone.0018850.

Davison, A. C., and D. V. Hinkley. 1997. “Bootstrap Methods and Their Application,” October. https://doi.org/10.1017/cbo9780511802843.

Franses, Philip Hans. 2016. “A Note on the Mean Absolute Scaled Error.” International Journal of Forecasting 32 (1): 20–22. https://doi.org/10.1016/j.ijforecast.2015.03.008.

Frazier, Peter I. 2018. “A Tutorial on Bayesian Optimization.” https://doi.org/10.48550/ARXIV.1807.02811.

Friedman, Jerome H. 2001. “Greedy Function Approximation: A Gradient Boosting Machine.” The Annals of Statistics 29 (5). https://doi.org/10.1214/aos/1013203451.

Gentleman, Robert, Vincent Carey, Wolfgang Huber, Sandrine Dudoit, and Rafael Irizarry. 2005. Bioinformatics and Computational Biology Solutions Using R and Bioconductor. Springer.

Hill, Andrew A, Peter LaPan, Yizheng Li, and Steve Haney. 2007. “Impact of Image Segmentation on High-Content Screening Data Quality for SK-BR-3 Cells.” BMC Bioinformatics 8 (1). https://doi.org/10.1186/1471-2105-8-340.

Hosmer, David W., and Stanley Lemeshow. 2000. Applied Logistic Regression. John Wiley & Sons, Inc. https://doi.org/10.1002/0471722146.

Hyndman, Rob J., and Anne B. Koehler. 2006. “Another Look at Measures of Forecast Accuracy.” International Journal of Forecasting 22 (4): 679–88. https://doi.org/10.1016/j.ijforecast.2006.03.001.

Hyndman, Robin John, and George Athanasopoulos. 2018. Forecasting: Principles and Practice. 2nd ed. Australia: OTexts.

Johnson, Dan, Phoebe Eckart, Noah Alsamadisi, Hilary Noble, Celia Martin, and Rachel Spicer. 2018. “Polar Auxin Transport Is Implicated in Vessel Differentiation and Spatial Patterning During Secondary Growth in Populus.” American Journal of Botany 105 (2): 186–96. https://doi.org/10.1002/ajb2.1035.

Joseph, V. Roshan. 2022. “Optimal Ratio for Data Splitting.” Statistical Analysis and Data Mining: The ASA Data Science Journal 15 (4): 531–38. https://doi.org/10.1002/sam.11583.

Joseph, V. Roshan, Evren Gul, and Shan Ba. 2015. “Maximum Projection Designs for Computer Experiments.” Biometrika 102 (2): 371–80. https://doi.org/10.1093/biomet/asv002.

Khun, M., and K. Johnson. 2013. Applied Predictive Modeling. New York: Springer.

Kim, Jungsu, Jacob M. Basak, and David M. Holtzman. 2009. “The Role of Apolipoprotein E in Alzheimer’s Disease.” Neuron 63 (3): 287–303. https://doi.org/10.1016/j.neuron.2009.06.026.

Kirkpatrick, S., C. D. Gelatt, and M. P. Vecchi. 1983. “Optimization by Simulated Annealing.” Science 220 (4598): 671–80. https://doi.org/10.1126/science.220.4598.671.

Koklu, Murat, and Ilker Ali Ozkan. 2020. “Multiclass Classification of Dry Beans Using Computer Vision and Machine Learning Techniques.” Computers and Electronics in Agriculture 174 (July): 105507. https://doi.org/10.1016/j.compag.2020.105507.

Kuhn, Max, and Kjell Johnson. 2019. Feature Engineering and Selection. Chapman; Hall/CRC. https://doi.org/10.1201/9781315108230.

———. 2021. Feature Engineering and Selection: A Practical Approach for Predictive Models. Taylor & Francis Group.

Kuhn, Max, and Hadley Wickham. 2020. “Tidymodels: A Collection of Packages for Modeling and Machine Learning Using Tidyverse Principles.” https://www.tidymodels.org.

Kvalseth, Tarald O. 1985. “Cautionary Note about R2.” The American Statistician 39 (4): 279–85. https://doi.org/10.2307/2683704.

Laarhoven, Peter J. M. van, and Emile H. L. Aarts. 1987. “Simulated Annealing.” In, 7–15. Springer Netherlands. https://doi.org/10.1007/978-94-015-7744-1_2.

Maron, Oded, and Andrew Moore. 1993. “Hoeffding Races: Accelerating Model Selection Search for Classification and Function Approximation.” In Advances in Neural Information Processing Systems, edited by J. Cowan, G. Tesauro, and J. Alspector. Vol. 6. Morgan-Kaufmann.

McKay, M. D., R. J. Beckman, and W. J. Conover. 1979. “A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code.” Technometrics 21 (2): 239. https://doi.org/10.2307/1268522.

Menardi, Giovanna, and Nicola Torelli. 2012. “Training and Assessing Classification Rules with Imbalanced Data.” Data Mining and Knowledge Discovery 28 (1): 92–122. https://doi.org/10.1007/s10618-012-0295-5.

Mingqiang, Yang, Kpalma Kidiyo, and Ronsin Joseph. 2008. “A Survey of Shape Feature Extraction Techniques.” In. InTech. https://doi.org/10.5772/6237.

Schulz, Eric, Maarten Speekenbrink, and Andreas Krause. 2016. “A Tutorial on Gaussian Process Regression: Modelling, Exploring, and Exploiting Functions.” http://dx.doi.org/10.1101/095190.

Shahriari, Bobak, Kevin Swersky, Ziyu Wang, Ryan P. Adams, and Nando de Freitas. 2016. “Taking the Human Out of the Loop: A Review of Bayesian Optimization.” Proceedings of the IEEE 104 (1): 148–75. https://doi.org/10.1109/jproc.2015.2494218.

Shewry, M. C., and H. P. Wynn. 1987. “Maximum Entropy Sampling.” Journal of Applied Statistics 14 (2): 165–70. https://doi.org/10.1080/02664768700000020.

Thomas, Rachel, and David Uminsky. 2020. “The Problem with Metrics Is a Fundamental Problem for AI.” https://doi.org/10.48550/ARXIV.2002.08512.

Wickham, Hadley, Mara Averick, Jennifer Bryan, Winston Chang, Lucy D’Agostino McGowan, Romain François, Garrett Grolemund, et al. 2019. “Welcome to the Tidyverse.” Journal of Open Source Software 4 (43): 1686. https://doi.org/10.21105/joss.01686.

Xu, Qing-Song, and Yi-Zeng Liang. 2001. “Monte Carlo Cross Validation.” Chemometrics and Intelligent Laboratory Systems 56 (1): 1–11. https://doi.org/10.1016/s0169-7439(00)00122-2.

Yeh, I.-Cheng. 2006. “Analysis of Strength of Concrete Using Design of Experiments and Neural Networks.” Journal of Materials in Civil Engineering 18 (4): 597–604. https://doi.org/10.1061/(ASCE)0899-1561(2006)18:4(597).