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The wealthiest passenger wasJohn Jacob AstorIV, heir to the Astor family fortune, who had made waves a year earlier by marrying 18-year-old Madeleine Talmadge Force, a young woman 29 years his junior, shortly after divorcing his first wife. ...
# 使用模型进行测试数据预测 pred_Y = model.predict(pred_X) # 将pred_Y即预测结果的值转换为整型 pred_Y = pred_Y.astype(int) # 提取乘客id passenger_id = full.loc[sourcerow:,'PassengerId'] # # 数据框:乘客ID,预测生存情况的值 predDf = pd.DataFrame({'PassengerId': passenger_id, 'Survi...
6. The Passenger List All life is of equal value, but sadly one cannot avoid the fact that the lives of the rich and famous attract more media attention than the lives of the ordinary man and woman in the street. A ship which goes down full of unknown ordinary Joes may well be just...
" It was not unusual for this to occur though and Evans was not upset by it, Titanic had a wealthy passenger list and a lot of private traffic to send. Evans turned off his set and went to bed around 11:30. If he had stayed on the air for another half hour or had sent the ...
Titanic: Directed by Jean Negulesco. With Clifton Webb, Barbara Stanwyck, Robert Wagner, Audrey Dalton. An unhappily married couple struggle to deal with their problems while on board the luxurious, ill-fated RMS Titanic.
数据集包含11个变量:PassengerID、Pclass、Name、Sex、Age、SibSp、Parch、Ticket、Fare、Cabin、Embarked,通过这些数据来预测乘客在Titanic事故中是否幸存下来。 3. 算法简介: 这一节中简单介绍一下逻辑回归,虽然名字中有回归,但其实逻辑回归是经典的分类算法,属于对数线性模型。
Titanic数据集是Kaggle上参与人数最多的项目之一。数据本身简单小巧,适合初学者上手,深入了解比较各个机器学习算法。 数据集包含11个变量:PassengerID、Pclass、Name、Sex、Age、SibSp、Parch、Ticket、Fare、Cabin、Embarked,通过这些数据来预测乘客在Titanic事故中是否幸存下来。
If you are interested in doing some survival analysis at the individual passenger level, see the Kaggle Titanic competition. (If I were doing it I would probably use a Gradient Boosting Machine solution, but it's way down my list of things to do. If you are interested, try it.) Finally...
pred_Y = pred_Y.astype(int) passenger_id = full.loc[sourceRow:,'PassengerId'] predDf = pd.DataFrame( {'PassengerId':passenger_id, 'Survived':pred_Y}) predDf.shape predDf.head() predDf.to_csv('titanic_pred.csv',index = False) 然后提交kaggle,最终...