Article published In:
International Journal of Corpus Linguistics
Vol. 26:2 (2021) ► pp.248283
References (56)
Baayen, R. H.
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. DOI logoGoogle 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. DOI logoGoogle Scholar
Bates, D., Mächler, M., Bolker, B., & Walker, S.
(2014) Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 671, 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]. [URL]
Breiman, L.
(2001) Random forests. Machine Learning, 45(1), 5–32. DOI logoGoogle Scholar
Bybee, J., & Thompson, S.
(2000) Three frequency effects in syntax. Berkeley Linguistics Society, 23(1), 378–388. DOI logoGoogle 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. DOI logoGoogle Scholar
Comrie, B.
(1985) Tense. Cambridge University Press. DOI logoGoogle 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. [URL]
Davies, M.
(2016) Corpus del Español/ Web Dialects 2 billion words. Available online at [URL]
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. DOI logoGoogle 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]. [URL]
DeMello, G.
(1993) –ra vs. –se subjunctive: A new look at an old topic. Hispania, 76(2), 235–243. DOI logoGoogle Scholar
Fox, J.
(1987) Effect displays for generalized linear models. Sociological Methodology, 171, 347–361. DOI logoGoogle Scholar
(2003) Effect displays in R for generalised linear models. Journal of Statistical Software, 8(15), 1–27. DOI logoGoogle 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. DOI logoGoogle 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. DOI logoGoogle Scholar
(2019) An R Companion to Applied Regression (3rd ed.). Sage. [URL]
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. [URL]. DOI logo
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. DOI logoGoogle 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. [URL]
He, H. & Garcia, E. A.
(2009) Learning from imbalanced data. IEEE Transactions on Knowledge & Data Engineering, 21(9), 1263–1284. DOI logoGoogle Scholar
Hothorn, T., Bühlmann, P., Dudoit, S., Molinaro, A., & Van Der Laan, M. J.
(2005) Survival ensembles. Biostatistics, 7(3), 355–373. DOI logoGoogle Scholar
Krawczyk, B.
(2016) Learning from imbalanced data: Open challenges and future directions. Progress in Artificial Intelligence, 5(4), 221–232. DOI logoGoogle 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. DOI logoGoogle 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, 611, 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, 2501, 113–141. DOI logoGoogle 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. DOI logoGoogle 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. DOI logoGoogle 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. [URL]
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. [URL]
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. DOI logoGoogle 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. DOI logoGoogle 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. [URL]
(2010) Temporal concord and Latin American Spanish dialects: A genetic blueprint. Revista Iberoamericana de Lingüística, 51, 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). DOI logoGoogle Scholar
Strobl, C., Boulesteix, A. L., Kneib, T., Augustin, T., & Zeileis, A.
(2008) Conditional variable importance for random forests. BMC Bioinformatics, 9(1). DOI logoGoogle Scholar
Suñer, M., & Padilla-Rivera, J.
(1987) Sequence of tenses and the subjunctive. Hispania, 70(3), 634–642. DOI logoGoogle Scholar
Tharwat, A.
(2020) Classification of assessment methods. Applied Computing and Informatics. Advance online publication. DOI logoGoogle Scholar
Venables, W. N., & Ripley, B. D.
(2002) Random and mixed effects. In Modern Applied Statistics with S (pp. 271–300). Springer. DOI logoGoogle 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. DOI logoGoogle Scholar
Wurmbrand, S.
(2014) Tense and aspect in English infinitives. Linguistic Inquiry, 45(3), 403–447. DOI logoGoogle Scholar
Cited by (1)

Cited by 1 other publications

Rosemeyer, Malte
2023. Chapter 9. Syntactic priming and individual preferences. In Free Variation in Grammar [Studies in Language Companion Series, 234],  pp. 260 ff. DOI logo

This list is based on CrossRef data as of 4 july 2024. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers. Any errors therein should be reported to them.