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Trying to predict survival rate of passengers using algorithms like Logistic Regression, Ada Boost, Gradient Boost , Decision Tree Classifiers , Extra Tree Classifiers , Random Forest Classifiers and XG Boost with appropriate data preprocessing techniques.

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decision-tree-classifiers extra-tree-classifiers random-forest-classifiers titanic-survival-predictor xg-boost python python3 machine-learning machine-learning-algorithms scikit-learn

titanic-survival-predictor's Introduction

Titanic-Survival-Predictor

Trying to predict survival rate of passengers using algorithms like Logistic Regression, Ada Boost, Gradient Boost , Decision Tree Classifiers , Extra Tree Classifiers , Random Forest Classifiers and XG Boost with appropriate data preprocessing techniques.

Format/columns of dataset

PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked

Survival 0 = No , 1 = Yes

sibsp = Number of siblings/spouses

parch = Number of parents/children

embarked = Port of Embarkation : C = Cherbourg, Q = Queenstown, S = Southampton

pclass = socio-economic status : 1st = Upper , 2nd = Middle ,3rd = Lower

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