Group Lasso for Identifying Tuberculosis Influenced Factors in West Java

نویسندگان

چکیده

Tuberculosis (TB) is a disease caused by bacteria that can affect serious infection in the lungs. It spread from one person to another through tiny droplets released into air via coughs and sneezes. West Java of locations with largest TB sufferer Indonesia. This research used number cases data 2017 identify group factors influence infections. The applied include health factor, environment facility demography factor. method this was lasso. After have been identified, ordinary least square determine significant infections based on these factors. selected factor cases. Furthermore, diarrhea sufferers, unemployment, malnutrition sufferers were be variables important square.

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

a framework for identifying and prioritizing factors affecting customers’ online shopping behavior in iran

the purpose of this study is identifying effective factors which make customers shop online in iran and investigating the importance of discovered factors in online customers’ decision. in the identifying phase, to discover the factors affecting online shopping behavior of customers in iran, the derived reference model summarizing antecedents of online shopping proposed by change et al. was us...

15 صفحه اول

Identifying Genetic Risk Factors via Sparse Group Lasso with Group Graph Structure

Genome-wide association studies (GWA studies or GWAS) investigate the relationships between genetic variants such as single-nucleotide polymorphisms (SNPs) and individual traits. Recently, incorporating biological priors together with machine learning methods in GWA studies has attracted increasing attention. However, in real-world, nucleotide-level bio-priors have not been well-studied to date...

متن کامل

Online Learning for Group Lasso

We develop a novel online learning algorithm for the group lasso in order to efficiently find the important explanatory factors in a grouped manner. Different from traditional batch-mode group lasso algorithms, which suffer from the inefficiency and poor scalability, our proposed algorithm performs in an online mode and scales well: at each iteration one can update the weight vector according t...

متن کامل

Adaptive Lasso and group-Lasso for functional Poisson regression

High dimensional Poisson regression has become a standard framework for the analysis of massive counts datasets. In this work we estimate the intensity function of the Poisson regression model by using a dictionary approach, which generalizes the classical basis approach, combined with a Lasso or a group-Lasso procedure. Selection depends on penalty weights that need to be calibrated. Standard ...

متن کامل

Group Lasso with Overlaps: the Latent Group Lasso approach

We study a norm for structured sparsity which leads to sparse linear predictors whose supports are unions of predefined overlapping groups of variables. We call the obtained formulation latent group Lasso, since it is based on applying the usual group Lasso penalty on a set of latent variables. A detailed analysis of the norm and its properties is presented and we characterize conditions under ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Forum Statistika dan Komputasi

سال: 2021

ISSN: ['0853-8115']

DOI: https://doi.org/10.29244/icsa.2019.pp18-28