Application of Exploratory Data Analysis to Generate Inferences on the Occurrence of Breast Cancer using a Sample Dataset

Exploratory Data Analysis (EDA) is a data analysis technique that can be used to visually represent the knowledge embedded deep in the given data set. The application of this technique can be used in medical data processing for the betterment of the offered services of healthcare providers. In women, breast cancer has become prevalent and requires proper methods to identify the possibility of occurrence at an early stage for treatment and cure. In this context, visualization technique of EDA can be applied to the existing datasets for learning and prediction. In this research work, the analysis aims on finding predominant features which would be helpful in predicting whether the tumor is benign or malignant. To achieve this goal various graphical techniques are used for a better visual understanding. Based on the results obtained it can be found that EDA plays a significant role in describing the data using statistical and visualization analysis without making any speculations about the content. With this dataset and EDA approach we have achieved a clear understanding about the significant features needed to predict if the tumor is benign or malignant.