  Data mining involves the systematic analysis of large data sets, and data
mining in agricultural soil datasets is exciting and modern research area. The
productive capacity of a soil depends on soil fertility. Achieving and
maintaining appropriate levels of soil fertility, is of utmost importance if
agricultural land is to remain capable of nourishing crop production. In this
research, Steps for building a predictive model of soil fertility have been
explained.
  This paper aims at predicting soil fertility class using decision tree
algorithms in data mining . Further, it focuses on performance tuning of J48
decision tree algorithm with the help of meta-techniques such as attribute
selection and boosting.
