Given a real-life Titanic data set, the program will predict who among a list of passengers survived the sinking of the Titanic (taking their Room Numbers, Floor, Patch, Cabin, and Age into consideration).
The modeling project delves into implementing the K-Nearest-Neighbor Algorithm by fitting and predicting target attributes via making testing and training data sets for k-fold cross-validations and 1-NN algorithms using Python libraries and custom Python classes!
The program primarily revolves around our understanding and implementation regarding preprocessing data, avoiding data leakage, and making models from pre-defined classes.