{"title":"Claus Weihs","description":"\u003cp\u003eClaus Weihs offers insightful works at the intersection of linguistics and data analysis, with a particular emphasis on the study of World Englishes and sociolinguistic phenomena. His books delve into advanced methodologies, such as optimising decision trees, to uncover patterns within complex language data.\u003c\/p\u003e\n\n\u003cp\u003eReaders interested in education, reference, and the quantitative study of language will find Weihs’ texts valuable for both theoretical understanding and practical application. His approach blends rigorous analysis with a focus on sociolinguistic diversity, appealing to scholars and students alike.\u003c\/p\u003e","products":[{"product_id":"optimizing-decision-trees-for-the-analysis-of-world-englishes-and-sociolinguistic-data-by-claus-weihs-9781009470315","title":"Optimizing Decision Trees for the Analysis of World Englishes and Sociolinguistic Data","description":"\u003cdiv class=\"book-description\"\u003e\n\u003cp\u003eThis Element introduces \u003cem\u003ePrInDT\u003c\/em\u003e (Prediction and Interpretation in Decision Trees), a statistical approach for modelling relationships between extra- and intralinguistic variables in World Englishes. It is based on decision trees and controls their size in a way that they are easy and straightforward to interpret.\u003c\/p\u003e\n\n\u003cp\u003eFurthermore, \u003cem\u003ePrInDT\u003c\/em\u003e optimises their accuracy so that they best fit the data and can be reliably used for prediction. Moreover, it can handle unbalanced classes that occur, for example, when comparing non-standard with standard linguistic realisations.\u003c\/p\u003e\n\n\u003cp\u003eThe various \u003cem\u003ePrInDT\u003c\/em\u003e functions can deal with classification and regression tasks and can analyse multiple endogenous variables jointly, even for models combining classification and regression. The authors introduce these features in some detail and apply them to World Englishes and sociolinguistic datasets.\u003c\/p\u003e\n\n\u003cp\u003eAs examples, they draw on L1 child data from England and Singapore as well as linguistic landscapes data from the Eastern Caribbean island of St. Martin.\u003c\/p\u003e\n\u003c\/div\u003e","brand":"Unknown","offers":[{"title":"Default Title","offer_id":47934163189996,"sku":"9781009470315","price":234.0,"currency_code":"NZD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0705\/7784\/8556\/files\/9781009470315-optimizing-decision-trees-for-the-analysis-of-world-englishes-and-sociolinguistic-data.jpg?v=1783901355"}],"url":"https:\/\/bookhero.pro\/collections\/claus-weihs.oembed","provider":"Book Hero","version":"1.0","type":"link"}