Predicting the Probability of Whether It Would Rain in Canberra Tomorrow - Statistics Project Example

Table of contents 1.0 Executive Summary 0 2.0Introduction 2 3.1 Data Preparation 4 3.2Data Pre-processing 4 3.3Variable Analysis 4 3.4Modeling 4 4.0Result 5 4.1Missing Values 5 4.2Outliers 5 4.3Variable Analysis 7 4.4Model Building 9 4.4.1Decision Tree: 9 4.4.2Random Forest 11 4.5Evaluation of Models 12 4.5.1Confusion Matrix 13 4.5.2Matthews correlation coefficient 13 4.5.3Precision, Recall and Specificity 14 4.5.4ROC Curve 14 5.0Discussion 15 6.0Conclusion 15 7.0 Reference 16 1.0 Executive Summary This assignment involved development of a predictive model by making use of a data from Canberra weather measurements in predicting the probability of whether it would rain tomorrow. The data used was obtained from Australian Bureau of Meteorology. A variety of softwares tools were utilized in the actualization of data mining of weather dataset. Decision Tree, Random Forest were the two models that were originated and appraised by used of Rattle a software tool utilized in prediction of rain tomorrow. The dataset consisted of 13 months’ weather in Sydney New South Wales from 1/7/2013 to 18/7/2012 which was obtained online from the Australian Bureau of Meteorology Website. There was renaming of columns with shorter names being given that are easy to understand and this would make it easy for manipulation in the software tools which were used. A correlation test was done and the strongest negative correlation was between “cloudnine” and sunshine where the Pearson correlation was -0.727.The main path through the decision tree is to the right, where there is a 88% of possibility of rain tomorrow if 9am humidity Read More