Construction of Decision Tree for Insurance Policy System through Entropy and Gini Index
Narander Kumar, Vishal Verma, Vipin Saxena · International Journal of Computer Applications · 2013
In the modern age of computing, sparse and irregularity in a sample of data is needed for reconstruction of the large and different types of dimensions of data.However, there is a challenge to analyze this type of data.One issue is the robust selection of data.There are many analytical tools are available but crucial part is the decomposition, and make the clusters as well as gradient estimated of data.When one extracts the attributes of sparsely sample data then most likely common attributes may lead to inaccurate results.Due to these, the present paper consists of the solutions through entropy calculation and GINI Index calculation of an insurance company.After calculation of entropy and GINI Index, a decision tree of sample data of an insurance company is presented.