[PDF][PDF] A Novel Cleansing Method for Random-Walk Data using Extended Multivariate Nonlinear Regression: A Data Preprocessor for Load Forecasting Mechanism

H Bakiri, H Ndyetabura, L Massawe… - International Journal of …, 2021 - researchgate.net
The efficiency of any load forecasting mechanism depends on the quality and distribution
characteristics of the training data. Outliers and missing values are the primary concern …

[HTML][HTML] XU-NetI: Simple U-shaped encoder-decoder network for accurate imputation of multivariate missing data

F Firdaus, S Nurmaini, B Tutuko, MN Rachmatullah… - Franklin Open, 2024 - Elsevier
Patients in intensive care unit (ICU) often have multiple vital signs monitored continuously.
However, missing data is common in ICU settings, negatively impacting clinical decision …

[PDF][PDF] FEATURE CLASSIFICATION BASED ON HETEROGENOUS DATA USING HYBRID MACHINE LEARNING: A REVIEW

A NURSIKUWAGUS, H PURWANTO… - Journal of Theoretical and …, 2023 - jatit.org
Heterogeneous data is a dataset with various types including data type and data source.
Classification of heterogeneous data is still becoming a discussion in research in the field of …

Verification of unemployment benefits' claims using Classifier Combination method

R Dehklharghani, H Emami - Signal and Data Processing, 2023 - jsdp.rcisp.ac.ir
Unemployment insurance is one of the most popular insurance types in the modern world.
The Social Security Organization is responsible for checking the unemployment benefits of …

[PDF][PDF] Year of Publication: 2021

H Bakiri, H Ndyetabura, L Massawe, H Maziku - 2021 - academia.edu
The efficiency of any load forecasting mechanism depends on the quality and distribution
characteristics of the training data. Outliers and missing values are the primary concern …