2025, Vol. 6, Issue 1, Part B

The paper looks into the various aspects of data mining, primarily the cleaning and preparation phase. A majority of the work required to be done while doing any analysis on a given dataset is its cleaning and preparation. Various approaches of cleaning the data include handling null values, missing values, outliers, anomalies and balancing the dataset. However, these are a few approaches amongst numerous others which need consulting from the domain expert.

This paper looks at the airline dataset which consists of one main dataset and three supplemental datasets that link the names of carriers, the airplane details, and the airport details. But, the dataset is not clean at all. To achieve the goal of predicting whether a flight will be diverted or not, this data needs to be cleaned and balanced. The paper will dive deeper into the process of the preparation of data and the final results of determining whether a flight will be diverted or not.