EDA for Multi-Class Prediction of Cirrhosis Outcomes (kaggle dataset) Gain Domain knowledge Check for missing values Check for duplicates Categorical features distribution Association between categorical features (Chi-square test) Numerical features distribution (histograms, boxplots, violinplot) Correlation between Numerical features Transformation of numerical features and Normality tests (Log Normal, QuantileTransformer, Boxcox transformation, Kolmogorov-Smirnov test, qqplots) Encoding values ( ordinal_encoder, label_encoder, one_hot_encoding) Correlation between all features PCA (Explained Variance and Cumulative Variance, loadings)