Quasi-optimality under pseudo f statistic in clustering data

Hochin, Teruhisa; Hayashi, Yoshihiro; Nomiya, Hiroki; Chowdhury, Mihir

doi:10.14419/ijet.v7i2.28.13205

Cited by 2 publications

(1 citation statement)

References 8 publications

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“…Cluster validity is measured using the Calinski-Harabasz pseudo F-statistic, which is a ratio reflecting intra-group similarity and inter-group dissimilarity [42,43]. Larger values of the pseudo F-statistic represent stronger intra-class group ties and more dispersed inter-group distances, i.e., better clustering results.…”

Section: Assessment Of Optimal Number Of Groups (Calculation Of Pseud...mentioning

confidence: 99%

Cropland Zoning Based on District and County Scales in the Black Soil Region of Northeastern China

Li,

Wang,

et al. 2024

Sustainability

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The black soil region of northeastern China, one of the world’s major black soil belts, is China’s main grain-producing area, producing a quarter of China’s commercial grain. However, over-exploitation and unsustainable management practices have led to a steady decline in the quality of arable land. Scientific and reasonable zoning of arable land is the key to ensuring that black soil arable land achieves sustainable development. In this study, the 317 districts and counties under the jurisdiction of Heilongjiang, Jilin, and Liaoning Provinces in the northeast region and the four eastern leagues of the Inner Mongolia Autonomous Region were taken as the study area, and arable land zoning in the northeast black soil region was explored through group analysis. Ten types of indicators were selected according to the four levels of climate, soil, vegetation, and topography of the northeast black soil region, including average precipitation and average temperature for many years at the climate level, organic matter content and soil texture (including clay, silt, and sand) at the soil level, NDVI and EVI indicators at the vegetation level, and DEM and slope indicators at the topographic level. In accordance with the principle of distinguishing differences and summarizing commonalities, nine scenarios of dividing the northeast black soil zones into 2 regions to 10 regions were explored, and these nine zoning scenarios were evaluated in terms of zoning. The results showed that (1) the spatial variability of cropland zoning in the northeast black soil zone based on four indicators, namely climate, soil, vegetation, and topography, was significant; (2) the results of the nine types of zoning based on cropland in the northeast black soil zone showed that intra-zonal zoning was optimal when zoning the northeast black soil zone into six types of zones, which enhanced the variability between the zones and the consistency within the zones; and (3) the assessment of large-scale cropland zoning using the pseudo F-statistic and area-weighted standard deviation methods revealed similarities in their outcomes. The results provide a scientific basis for the subregional protection of arable land in the black soil zone and help to formulate effective policies for different regions.

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Section: Assessment Of Optimal Number Of Groups (Calculation Of Pseud...mentioning

confidence: 99%

Cropland Zoning Based on District and County Scales in the Black Soil Region of Northeastern China

Li,

Wang,

et al. 2024

Sustainability

View full text Add to dashboard Cite

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Fuzzy C-Means for Regional Clustering in East Java Province Based on Human Development Index Indicators

Qori'atunnadyah

2023

J Statistika

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The Human Development Index (HDI) is the UN's key metric for gauging human advancement within a country, blending vital elements like per capita income, life expectancy, and education. In Indonesia, the HDI assesses societal well-being, with East Java's HDI lagging behind national and governmental targets despite mitigation efforts. To address this, the study utilizes Fuzzy C-Means clustering to classify East Java's regions based on HDI indicators, revealing five optimal groups via pseudo-F-statistic analysis. One-way MANOVA confirms variations among these groups, while One-Way ANOVA validates the significance of the four HDI indicators in categorization. The HDI-based categorization denotes Group 3 as high-status, Group 1 as low-status, Group 2 as moderately high-status, Group 4 as moderate, and Group 5 as moderately low-status. Consequently, it's advised that the government concentrates on improving low-HDI groups to uplift East Java's populace. This research can serve as a cornerstone for policymakers and stakeholders in their efforts to enhance the HDI in this region.

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Quasi-optimality under pseudo f statistic in clustering data

Cited by 2 publications

References 8 publications

Cropland Zoning Based on District and County Scales in the Black Soil Region of Northeastern China

Cropland Zoning Based on District and County Scales in the Black Soil Region of Northeastern China

Fuzzy C-Means for Regional Clustering in East Java Province Based on Human Development Index Indicators

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