Do you want to publish a course? Click here

Regression Analysis of Lexical and Morpho-Syntactic Properties of Kiezdeutsch

تحليل الانحدار للعقارات المعجمية والمورفخنة من Kiezdeutsch

212   0   0   0.0 ( 0 )
 Publication date 2021
and research's language is English
 Created by Shamra Editor




Ask ChatGPT about the research

Kiezdeutsch is a variety of German predominantly spoken by teenagers from multi-ethnic urban neighborhoods in casual conversations with their peers. In recent years, the popularity of Kiezdeutsch has increased among young people, independently of their socio-economic origin, and has spread in social media, too. While previous studies have extensively investigated this language variety from a linguistic and qualitative perspective, not much has been done from a quantitative point of view. We perform the first large-scale data-driven analysis of the lexical and morpho-syntactic properties of Kiezdeutsch in comparison with standard German. At the level of results, we confirm predictions of previous qualitative analyses and integrate them with further observations on specific linguistic phenomena such as slang and self-centered speaker attitude. At the methodological level, we provide logistic regression as a framework to perform bottom-up feature selection in order to quantify differences across language varieties.

References used
https://aclanthology.org/
rate research

Read More

The span-based model enjoys great popularity in recent works of sequence segmentation. However, each of these methods suffers from its own defects, such as invalid predictions. In this work, we introduce a unified span-based model, lexical unit analy sis (LUA), that addresses all these matters. Segmenting a lexical unit sequence involves two steps. Firstly, we embed every span by using the representations from a pretraining language model. Secondly, we define a score for every segmentation candidate and apply dynamic programming (DP) to extract the candidate with the maximum score. We have conducted extensive experiments on 3 tasks, (e.g., syntactic chunking), across 7 datasets. LUA has established new state-of-the-art performances on 6 of them. We have achieved even better results through incorporating label correlations.
The real estate valuation is the process of estimating the real estate price based on the real estate description and property features . The aim of this research is to define the main variables and study their effects on defining the price of the residential real estates in Damascus, hence to build a mathematical model based on Multiple Regression Analysis method for the valuation of these Real Estates Data on 130 residential real estates in Damascus were collected and analyzed using the SPSS package . The Analyses have revealed that it is possible to rely on the Multiple Regression Analyses model to estimate the price of the real estate but only after defining and testing its shortcomings and transforming the model into Multiple – Non linear Regression model . This research concluded that the relationship between the price of the real estate and the studied variables is nonlinear .
Linear regression methods impose strong constraints on regression models, especially on the error terms where it assumes that it is independent and follows normal distribution, and this may not be satisfied in many studies, leading to bias that can not be ignored from the actual model, which affects the credibility of the study. We present in this paper the problem of estimating the regression function using the Nadarya Watson kernel and k- nearest neighbor estimators as alternatives to the parametric linear regression estimators through a simulation study on an imposed model, where we conducted a comparative study between these methods using the statistical programming language R in order to know the best of these estimations. Where the mean squares errors (MSE) was used to determine the best estimate. The results of the simulation study also indicate the effectiveness and efficiency of the nonparametric in the representation of the regression function as compared to linear regression estimators, and indicate the convergence of the performance of these two estimates.
The modern era is witnessing a tangible development in all fields of science . As a result of this development , there is a growing need for statistical methods to solve the problems facing workers in these fields.

suggested questions

comments
Fetching comments Fetching comments
Sign in to be able to follow your search criteria
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا