In terms of Linear Algebra, it is extremely common to use capital Latin letters for matrices (e.g. design matrix XX) and lowercase Latin letters for vectors (response vector yy). Usually X is a matrix of data values with multiple feature variables, having one column per feature variable. On the other hand, y is a vector of data values. so it has become a standard way to denote uppercase for X and lowercase for y in Python Model.
Let’s see an example:
df = pd.read_csv(‘D:\Datasets\haberman.csv’)
X = df.drop(‘status’,axis=’columns’)
y = df[‘status’]
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.30, random_state=1234)