期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2020
卷号：11
期号：5
DOI：10.14569/IJACSA.2020.0110557
出版社：Science and Information Society (SAI)
摘要：The historical geographical data of Kashmir province is spread across two disparate files having attributes of Maximum Temperature, Minimum Temperature, Humidity measured at 12 A.M., Humidity measured at 3 P.M., rainfall besides auxiliary parameters like date, year etc. The parameters Maximum Temperature, Minimum Temperature, Humidity measured at 12 A.M., Humidity measured at 3 P.M. are continuous in nature and here, in this study, we applied Information Gain and Gini Index on these attributes to convert continuous data into discrete values, their after we compare and evaluate the generated results. Of the four attributes, two have same results for Information Gain and Gini Index; one attribute has overlapping results while as only one attribute has conflicting results for Information Gain and Gini Index. Subsequently, continuous valued attributes are converted into discrete values using Gini index. Irrelevant attributes are not considered and auxiliary attributes are labeled accordingly. Consequently, the data set is ready for the application of machine learning (decision tree) algorithms.
关键词：Geographical data mining; information gain; Gini index; machine learning; decision tree
