Agriculture is a non-technical sector where in technology can be incorporated for the betterment. In this paper, the soil
test report values are used to classify several significant soil features like village wise soil fertility indices of Available
Phosphorus (P), Available Potassium (K), Organic Carbon (OC) and Boron (B), as well as the parameter Soil Reaction (pH).
The classification and prediction of the village wise soil parameters aids in reducing wasteful expenditure on fertilizer inputs,
increase profitability, save the time of chemical soil analysis experts, improves soil health and environmental quality. These five
classification problems are solved using the fast learning classification technique known as Extreme Learning Machine (ELM)
with different activation functions like Gaussian radial basis, sine-squared, hyperbolic tangent, triangular basis, and hard limit.
Keywords: Extreme Learning Machines, Activation functions, Soil, Confusion matrix and Parameters
