Systematic Review of Using Machine Learning in Imputing Missing Values

Missing data are a universal data quality problem in many domains, leading to misleading analysis and inaccurate decisions. Much research has been done to investigate the different mechanisms of missing data and the proper techniques in handling various data types. In the last decade, machine learni...

Deskribapen osoa

Gorde:

Xehetasun bibliografikoak
Egile Nagusiak:	Mustafa Alabadla, Fatimah Sidi, Iskandar Ishak, Hamidah Ibrahim, Lilly Suriani Affendey, Zafienas Che Ani, Marzanah A. Jabar, Umar Ali Bukar, Navin Kumar Devaraj, Ahmad Sobri Muda, Anas Tharek, Noritah Omar, M. Izham Mohd Jaya
Formatua:	Artigo
Hizkuntza:	Inglês
Argitaratua:	IEEE 2022-01-01
Saila:	IEEE Access
Gaiak:	Systematic literature review data imputation data mining missingness data preprocessing data quality
Sarrera elektronikoa:	https://ieeexplore.ieee.org/document/9762231/
Etiketak:	Etiketa erantsi Etiketarik gabe, Izan zaitez lehena erregistro honi etiketa jartzen!

Systematic Review of Using Machine Learning in Imputing Missing Values

Antzeko izenburuak