Dual Water Choices: The Assessment of the Influential Factors on Water Sources Choices Using Unsupervised Machine Learning Market Basket Analysis
An unsupervised machine learning model of association rule known as market basket analysis is proposed in this study to analyze the influence of various socio-economic factors on the choice of the water source. Data of 51 socio-economic factors collected from 295 individuals living in 65 households...
Guardado en:
Autores principales: | Tiyasha Tiyasha, Suraj Kumar Bhagat, Firaol Fituma, Tran Minh Tung, Shamsuddin Shahid, Zaher Mundher Yaseen |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
IEEE
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/cf2f1979b63447efa7e307f14fc813c6 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Improving Unsupervised Domain Adaptive Re-Identification Via Source-Guided Selection of Pseudo-Labeling Hyperparameters
por: Fabian Dubourvieux, et al.
Publicado: (2021) -
Temporal feature adaptive non-intrusive load monitoring via unsupervised probability density evolution
por: Yu Liu, et al.
Publicado: (2021) -
Unsupervised Domain Adaptation Network With Category-Centric Prototype Aligner for Biomedical Image Segmentation
por: Ping Gong, et al.
Publicado: (2021) -
Automatic Unsupervised Fabric Defect Detection Based on Self-Feature Comparison
por: Zhengrui Peng, et al.
Publicado: (2021) -
Editorial: Unsupervised Learning Models for Unlabeled Genomic, Transcriptomic & Proteomic Data
por: Jianing Xi, et al.
Publicado: (2021)