Data analysis on deforestation
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Deforestation is a global phenomenon that threatens not only biodiversity but also the livelihoods of people who depend on them. Recent global analyses indicates that this problem is growing, hence the growing need to identify the underlying drivers in order to develop more responsive policies. We present a machine learning-based method which automatically identifies key drivers and makes predictions from available spatial data in Swaziland during the post millennium period. The efficient Bayesian multivariate classifiers (EBMC) are used to learn feature-selected Bayesian network (BN) models of deforestation
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