3. Electronic Theses and Dissertations (ETDs) - All submissions

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    Evaluation of cluster analysis and latent class analysis in clustering
    (2019) Murisa, Tatenda
    The study compares the performance of latent class, K-means and hierarchical clustering on data with different degrees of cluster overlap. It also assesses how various standardisation methods affect the results of hierarchical and K-means clustering. Several distance and agglomeration methods are evaluated to observe how they perform depending on cluster overlap. Three artificial datasets were simulated whose clusters were poorly, moderately and well separated. These along with the seeds data were run through the three clustering methods. Several external validity indices were calculated for each cluster solution. The adjusted Rand index was used for comparison in the discussion because it is not affected by the number of clusters. Results showed that Ward’s method performed better compared to all other agglomeration methods and the Manhattan distance performed better across the different cluster types in hierarchical clustering. Latent class clustering performed better for poorly and well separated clusters. When the variance of the variables were comparable, K-means clustering with no standardisation performed well. Standardisation by the maximum value and z-score had the best cluster recovery when the variance of variables were large.
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    Development of a grassland monitoring system for the management of the wolkberg wilderness area.
    (1991) Coombes, Peter, John.
    This study aimed to investigate, within the contemporary philosophy of science, key aspects of the paradigm formulated by the national Vegetation Monitoring Work team (VMW), and thereby develop a grassland monitoring system to place. the management of the Wolkberg Wilderness Area (WWA) on a testable basis. ( Abbreviation abstract )
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    The relationship between pollen rain, vegetation, climate, meteorological factors and land-use in the PWV, Transvaal
    (1991) Cadman, Ann
    A two-year analysis of pollen rain was conducted in the Pretoria-Witwatersrand-Vereeniging district of the Transvaal, South Africa. Poaceae WaS the major component of the pollen assemblage, comprising 52% regionally. Of the total pollen count, 58.8% was non-seasonal and present throughout the year. During the analysis it became apparent that fungal spores dominated the atmospheric content, accounting for 94% of total airspora, considered here to incl ude pollen and fUngal spores.[Abbreviated Abstract. Open document to view full version].
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