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Predicting the Survival Rate of Titanic Disaster Using Machine Learning Approaches

机译:使用机器学习方法预测泰坦尼克号灾难的生存率

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The Titanic incident has led the scientist and investigators to comprehend what can have prompted the survival of a few travelers and death of the rest. Many machine learning algorithms contributed in predicting the survival rate of passengers. In addition to the this, a dataset of 891 rows which includes the attributes namely Age, PassengerID, Sex, Name, Embarked, Fare etc. has been used. In this paper, survival of passengers is figured out using various machine learning techniques namely decision tree, logistic regression and linear SVM. The main focus of this work is to differentiate between the three different machine learning algorithms to analyze the survival rate of traveller based on the accuracy.
机译:泰坦尼克号事件已导致科学家和研究人员理解了什么可能促使少数旅行者幸存下来,并导致其余人员死亡。许多机器学习算法有助于预测乘客的生存率。除此之外,还使用了891行的数据集,其中包括年龄,乘客ID,性别,姓名,登机,票价等属性。在本文中,使用各种机器学习技术(即决策树,逻辑回归和线性支持向量机)来计算乘客的生存率。这项工作的主要重点是区分三种不同的机器学习算法,以基于准确性分析旅行者的生存率。

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