Principal component and multiple correspondence analysis for handling mixed variables in the smoothed location model
The issue of classifying objects into groups when the measured variables are mixtures of continuous and binary variables has attracted the attention of statisticians. Among the discriminant methods in classification, Smoothed Location Model (SLM) is used to handle data that contains both continuous...
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| Format: | Thesis |
| Language: | eng eng |
| Published: |
2016
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| Online Access: | https://etd.uum.edu.my/6034/1/s817094_01.pdf https://etd.uum.edu.my/6034/2/s817094_02.pdf |
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