Article published in:
International Journal of Corpus Linguistics
Vol. 26:2 (2021) ► pp. 248283
References

References

Baayen, R. H.
(2010) Demythologizing the word frequency effect: A discriminative learning perspective. The Mental Lexicon, 5(3). 436–461. CrossrefGoogle Scholar
Baayen, R. H., Hendrix, P., & Ramscar, M.
(2011a, January 6–9). Sidestepping the combinatorial explosion: Towards a processing model based on discriminative learning [Paper presentation]. Annual Meeting of the Linguistic Society of America. Pittsburgh, USA.
Baayen, R. H., Milin, P., Filipovic Durffevic, D., Hendrix, P., & Marelli, M.
(2011b) An amorphous model for morphological processing in visual comprehension based on naive discriminative learning. Psychological Review, 118(3). 438. CrossrefGoogle Scholar
Baayen, R. H., Endresen, A., Janda, L. A., Makarova, A., & Nesset, T.
(2013) Making choices in Russian: Pros and cons of statistical methods for rival forms. Russian Linguistics, 37(3), 253–291. CrossrefGoogle Scholar
Bates, D., Mächler, M., Bolker, B., & Walker, S.
(2014) Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67, 1–48.Google Scholar
Bello, A., & Cuervo, R. J.
(1970) Gramática de la lengua castellana [A Grammar of the Spanish Language]. Sopena Argentina.Google Scholar
Branco, P., Ribeiro, R. P., & Torgo, L.
(2016) UBL: An R Package for Utility-Based Learning [Computer software]. http://​arxiv​.org​/abs​/1604​.08079
Breiman, L.
(2001) Random forests. Machine Learning, 45(1), 5–32. CrossrefGoogle Scholar
Bybee, J.
(1985) Morphology: A Study of the Relation between Meaning and Form. John Benjamins. CrossrefGoogle Scholar
Bybee, J., & Thompson, S.
(2000) Three frequency effects in syntax. Berkeley Linguistics Society, 23(1), 378–388. CrossrefGoogle Scholar
Carrasco Gutierrez, A.
(1998) La correlación de tiempos en español [Sequence of Tense in Spanish]. Universidad Complutense de Madrid dissertation.Google Scholar
Chawla, N. V., Japkowicz, N., & Kotcz, A.
(2004) Special issue on learning from imbalanced data sets. ACM Sigkdd Explorations Newsletter, 6(1), 1–6. CrossrefGoogle Scholar
Comrie, B.
(1985) Tense. Cambridge University Press. CrossrefGoogle Scholar
Crespo del Río, C.
(2014) Tense and Mood Cariation in Spanish Nominal Subordinates: The Case of Peruvian Varieties [Doctoral dissertation, University of Illinois at Urbana-Champaign). IDEALS. http://​hdl​.handle​.net​/2142​/49477
Davies, M.
(2016) Corpus del Español/ Web Dialects 2 billion words. Available online at http://​www​.corpusdelespanol​.org
Davis, J., & Goadrich, M.
(2006) The relationship between Precision-Recall and ROC curves. In Proceedings of the 23rd International Conference on Machine Learning (pp. 233–240). ACM. CrossrefGoogle Scholar
Day, M.
(2011 June 21). Variation in the use of the –ra and –se forms of the imperfect subjunctive in Modern Spoken Peninsular Spanish [Paper presentation]. NWAV 40, Georgetown University.
Debeer, D., & Strobl, C.
(2019) permimp: (Conditional) Permutation Importance (R package version 0.1–01) [Computer software]. https://​github​.com​/ddebeer​/permimp
DeMello, G.
(1993) –ra vs. –se subjunctive: A new look at an old topic. Hispania, 76(2), 235–243. CrossrefGoogle Scholar
Fox, J.
(1987) Effect displays for generalized linear models. Sociological Methodology, 17, 347–361. CrossrefGoogle Scholar
(2003) Effect displays in R for generalised linear models. Journal of Statistical Software, 8(15), 1–27. CrossrefGoogle Scholar
Fox, J., & Hong, J.
(2009) Effect displays in R for multinomial and proportional-odds logit models: Extensions to the effects package. Journal of Statistical Software, 32(1), 1–24. CrossrefGoogle Scholar
Fox, J., & Weisberg, S.
(2018) Visualizing fit and lack of fit in complex regression models with predictor effect plots and partial residuals. Journal of Statistical Software, 87(9), 1–27. CrossrefGoogle Scholar
(2019) An R Companion to Applied Regression (3rd ed.). Sage. http://​tinyurl​.com​/carbook
García, V., Mollineda, R. A., & Sánchez, J. S.
(2010) Theoretical analysis of a performance measure for imbalanced data. In 20th International Conference on Pattern Recognition (pp. 617–620). IEEE. https://​ieeexplore​.ieee​.org​/document​/5597459. Crossref
Gili Gaya, S.
(1983) Curso superior de sintaxis española [Advanced Course on Spanish Syntax]. Colton Book Imports.Google Scholar
Goldberg, A. E.
(1995) Constructions: A Construction Grammar Approach to Argument Structure. The University of Chicago Press.Google Scholar
Guajardo, G., & Goodall, G.
(2019) On the status of concordantia temporum in Spanish: An experimental approach. Glossa, 4(1), 116. CrossrefGoogle Scholar
He, H., Bai, Y., Garcia, E. A., & Li, S.
(2008) ADASYN: Adaptive synthetic sampling approach for imbalanced learning. In 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence), 1322–1328. IEEE. https://​t​.ly​/w1uy
He, H. & Garcia, E. A.
(2009) Learning from imbalanced data. IEEE Transactions on Knowledge & Data Engineering, 21(9), 1263–1284. CrossrefGoogle Scholar
Hothorn, T., Bühlmann, P., Dudoit, S., Molinaro, A., & Van Der Laan, M. J.
(2005) Survival ensembles. Biostatistics, 7(3), 355–373. CrossrefGoogle Scholar
Krawczyk, B.
(2016) Learning from imbalanced data: Open challenges and future directions. Progress in Artificial Intelligence, 5(4), 221–232. CrossrefGoogle Scholar
Laca, B.
(2010) The puzzle of subjunctive tenses. In R. Box-Bennema, B. Kampers-Manhe, & B. Hollebrandse (Eds.), Romance Languages and Linguistic Theory 2008: Selected Papers from ‘Going Romance’ Groningen 2008 (pp. 77–104). John Benjamins. CrossrefGoogle Scholar
Lapesa, R.
(1997) Historia de la Lengua Española [History of the Spanish Language]. Biblioteca Románica Hispánica.Google Scholar
Lathrop, T. A.
(1980) The Evolution of Spanish. Juan de la Cuesta.Google Scholar
Lopez Samaniego, A., & Kempas, I.
(2018) Querría que me lo compruebes/comprobaras/comprobases: Verb tense choice after expressions of attenuated volition in European Spanish. Estudios Filologicos, 61, 35–58.Google Scholar
López, V., Fernández, A., García, S., Palade, V., & Herrera, F.
(2013) An insight into classification with imbalanced data: Empirical results and current trends on using data intrinsic characteristics. Information Sciences, 250, 113–141. CrossrefGoogle Scholar
Lunn, P. V.
(1995) The evaluative function of the Spanish subjunctive. In J. Bybee & S. Fleischman (Eds.), Modality in Grammar and Discourse (pp. 429–449). John Benjamins. CrossrefGoogle Scholar
Naranjo, M. G.
(2017) The se-ra alternation in Spanish subjunctive. Corpus Linguistics and Linguistic Theory, 13(1), pp.97–134.Google Scholar
Olson, D. L., & Delen, D.
(2008) Performance evaluation for predictive modeling. In Advanced Data Mining Techniques (pp. 137–147). Springer. CrossrefGoogle Scholar
Penny, R.
(1991) A History of the Spanish Language. Cambridge University Press.Google Scholar
Picallo, C.
(1984) “El nudo FLEX y el parámetro del sujeto nulo” [The IP and pro-drop parameter]. In I. Bosque (Ed), Indicativo y subjuntivo [Indicative and Subjunctive] (pp. 202–233). Taurus.Google Scholar
Provost, F.
(2000) Machine learning from imbalanced data sets 101. In Proceedings of the AAAI’2000 Workshop on Imbalanced Data Sets. AAAI Press. https://​www​.aaai​.org​/Papers​/Workshops​/2000​/WS​-00​-05​/WS00​-05​-001​.pdf
Quer, J.
(1998) Mood at the Interface. Holland Academic Graphics.Google Scholar
R Core Team
(2019) R: A language and environment for statistical computing (Version 3.6.1) [Computer software]. R Foundation for Statistical Computing. http://​www​.R​-project​.org/
Raeder, T., Forman, G., & Chawla, N. V.
(2012) Learning from imbalanced data: Evaluation matters. In D. E. Holmes & J. C. Lakhmi (Eds.), Data Mining: Foundations and Intelligent Paradigms (pp. 315–331). Springer. CrossrefGoogle Scholar
Rosemeyer, M., & Schwenter, S. A.
(2019) Entrenchment and persistence in language change: The Spanish past subjunctive. Corpus Linguistics and Linguistic Theory, 15(1), 167–204. CrossrefGoogle Scholar
Sessarego, S.
(2008) Spanish concordantia temporum: An old issue, new solutions. In M. Westmoreland & J. A. Thomas (Eds.), Selected Proceedings of the 4th Workshop on Spanish Sociolinguistics (pp. 91–99). Cascadilla Proceedings Project. http://​www​.lingref​.com​/cpp​/wss​/4​/paper1759​.pdf
(2010) Temporal concord and Latin American Spanish dialects: A genetic blueprint. Revista Iberoamericana de Lingüística, 5, 137–169.Google Scholar
Strobl, C., Boulesteix, A. L., Zeileis, A., & Hothorn, T.
(2007) Bias in random forest variable importance measures: Illustrations, sources and a solution. BMC Bioinformatics, 8(1). CrossrefGoogle Scholar
Strobl, C., Boulesteix, A. L., Kneib, T., Augustin, T., & Zeileis, A.
(2008) Conditional variable importance for random forests. BMC Bioinformatics, 9(1). CrossrefGoogle Scholar
Suñer, M., & Padilla-Rivera, J.
(1987) Sequence of tenses and the subjunctive. Hispania, 70(3), 634–642. CrossrefGoogle Scholar
Tharwat, A.
(2020) Classification of assessment methods. Applied Computing and Informatics. Advance online publication. CrossrefGoogle Scholar
Venables, W. N., & Ripley, B. D.
(2002) Random and mixed effects. In Modern Applied Statistics with S (pp. 271–300). Springer. CrossrefGoogle Scholar
Wallace, B. C., & Dahabreh, I. J.
(2012) Class probability estimates are unreliable for imbalanced data (and how to fix them). In Institute of Electrical and Electronics Engineers (IEEE) 12th International Conference on Data Mining (International Conference on Data Mining) (pp. 695–704). IEEE Computer Society. CrossrefGoogle Scholar
Wurmbrand, S.
(2014) Tense and aspect in English infinitives. Linguistic Inquiry, 45(3), 403–447. CrossrefGoogle Scholar