Question

11. Split your data into train 80% train and 20% test, use the last two digits of your student number for the seed. Name the train/test dataframes as follows : X_train_firstname, X_test firstname, y_train firstname, y_test firstname.

Answer 1

The question pertains to splitting a dataset into training and test sets using a student's unique identifier as a seed, which is a common step in preparing data for machine learning modeling.

Step-by-step explanation:

The subject of the question relates to data splitting in the context of machine learning or data analysis. The student is asked to split their dataset into an 80% training set and a 20% test set using the last two digits of their student number as the seed for randomness. This is a common practice for preparing data for predictive modeling in order to evaluate the performance of an algorithm on unseen data.

To achieve the data split, you might use a function like train_test_split from the scikit-learn library in Python, for example. The train and test dataframes should be named using the student's first name, following a specific naming convention (X_train_firstname, X_test_firstname, y_train_firstname, y_test_firstname), where 'X' generally represents the feature data and 'y' usually stands for the labels or targets.

It is important to use the provided seed when splitting the data to ensure the reproducibility of your results. The use of the student's last two digits of their number as a seed adds a personal touch to the exercise, ensuring that each student's split is unique to their own identifier.