Classification Approach for Analysis of Weather Dataset with Different Training Strategies

Due to its extensive content, data mining has emerged as one of the newest areas of study. Finding hidden patterns in a database or other information repository is accomplished through data mining. In order to get knowledge from the patterns, these information is required. The primary objective is to find knowledge from the data. In order to ascertain the playing condition based on the present temperature measurements, we employ a data mining technique in this study termed classification. One effective method for grouping the dataset's characteristics into distinct classes is the classification technique. We employ categorization algorithms such as Random Tree, REP Tree, and Decision Tree (J48) in our methodology. The effectiveness of different categorization methods is then contrasted. We employ a set of open source machine learning algorithms called WEKA (Waikato Environment for Knowledge Analysis) as our tool.