泰坦尼克号灾难数据集的探索性数据分析和机器学习

Karman Singh, Renuka Nagpal, Rajni Sehgal
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引用次数: 8

摘要

泰坦尼克号是一艘英国游轮,据说是世界历史上最大的游轮。它在从南安普敦到纽约的首航途中撞上了一座冰山。船上有2200多名乘客,近一半的人在这场前所未有的灾难中丧生。这一臭名昭著的事件迫使研究人员深入研究数据集。这项研究旨在实现探索性数据分析,并了解一个人在船上生存的关键影响或参数。生存预测是通过应用各种算法,如逻辑回归,K近邻,支持向量机,决策树。最后,以表格形式比较了基于输入特征的算法的精度。
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Exploratory Data Analysis and Machine Learning on Titanic Disaster Dataset
RMS Titanic was a British cruise ship said to be the largest cruise ever made in the history of world. It collided with an iceberg during its maiden journey across the pacific ocean from Southampton to New York City. With more than 2200 passengers on board, nearly half of them died after the unprecedented mishap. The infamous incident compels researchers to dig into the dataset. This research is aimed at achieving an exploratory data analysis and understand the effect or parameters key to the survival of a person had they been on the ship. The survival prediction has been done by applying various algorithms like Logistic Regression, K – nearest neighbours, Support vector machines, Decision Tree. Towards the end, accuracies of the algorithms based on features fed to them has been compared in a tabular form.
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