Abstract: Agglomerative algorithms have been used in crime analysis to classify criminal activities and to classify areas into higher and lower criminal activities. The researches were mostly applying the algorithms on one particular distance measure. This study identifies the usefulness of applying different algorithms on different interval measures simultaneously for better classifications of crime data across the 36 states in Nigeria using statistical analysis supplemented with Geographical Information Systems (GIS) analysis.
Y. Bello, S.U. Gulumbe and S.A. Yelwa, 2012. Simultaneous Application of Agglomerative Algorithms on Interval Measures for Better Classification of Crime Data Across the States in Nigeria. Research Journal of Applied Sciences, 7: 41-47.