Editing Perl Data Language (section)

==Machine learning==
PDL can be used for [[machine learning]]. It includes modules that are used to perform classic [[k-means clustering]] or general and generalized linear modeling methods such as ANOVA, linear regression, PCA, and logistic regression. Examples of PDL usage for regression modelling tasks include evaluating association between education attainment and ancestry differences of parents,<ref name="pmid25734509">{{cite journal | vauthors = Abdellaoui A, Hottenga JJ, Willemsen G, Bartels M, van Beijsterveldt T, Ehli EA, Davies GE, Brooks A, Sullivan PF, Penninx BW, de Geus EJ, Boomsma DI | title = Educational Attainment Influences Levels of Homozygosity through Migration and Assortative Mating | journal = PLOS ONE | volume = 10 | issue = 3 | pages = e0118935 | date = Mar 2015 | pmid = 25734509 | pmc = 4347978 | doi = 10.1371/journal.pone.0118935 | bibcode = 2015PLoSO..1018935A | doi-access = free }}</ref> comparison of RNA-protein interaction profiles that needs regression-based normalization<ref name="pmid24398258">{{cite journal | vauthors = Wang T, Xie Y, Xiao G | title = dCLIP: a computational approach for comparative CLIP-seq analyses | journal = Genome Biology | volume = 15 | issue = 1 | pages = R11 | date = Jan 2014 | pmid = 24398258 | pmc = 4054096 | doi = 10.1186/gb-2014-15-1-r11 | doi-access = free }}</ref> and analysis of spectra of galaxies.<ref>{{cite journal | vauthors = Sánchez SF, Pérez E, Sánchez-Blázquez P, González JJ, Rosález-Ortega FF, Cano-Dí az M, López-Cobá C, Marino RA, Gil de Paz A, Mollá M, López-Sánchez AR, Ascasibar Y, Barrera-Ballesteros J | title = Pipe3D, a pipeline to analyze Integral Field Spectroscopy Data: I. New fitting philosophy of FIT3D | journal = Revista Mexicana de Astronomía y Astrofísica | volume = 52 | pages = 21–53 | date = April 2016 | arxiv = 1509.08552 | bibcode = 2016RMxAA..52...21S }}</ref>