TitanicClassification.py file contains the project based on binary classification. The dataset comprises the values of data related to passengers like name, age, gender, socio-economic status, etc., and a binary value of whether the passenger survived or not. The goal is to predict the survival of a passenger for the testing dataset. Techniques Used: Data preprocessing, mainly to handle invalid/missing values and categorical columns. Creative Feature Engineering. Data Visualization. Training on Random Forest Classifier and XGBoost Classifier machine learning models. Cross Validation metric for validation of the model.
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Abhishekkohli/Titanic-Disaster-Classification-ML
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TitanicClassification.py file contains project based on binary classification. The dataset comprises of data related to passengers and binary value of whether they survived or not.
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