【Kaggle】第一次提交 TitanicpythonMichael是个半路程序员-

项目官网地址

新手可以参考这篇 8、Getting Started With Titanic，教你如何操作、提交等

自己简要再记录一下：

• Join the competition
  
  各个 tab 下可以查看数据Data、代码编写Notebooks、讨论、排名、比赛规则、队伍
• 点击 Notebooks，新建文件
  
• 添加比赛数据集
  
• 编写代码

import numpy as np # linear algebra import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv) ​ import os for dirname, _, filenames in os.walk('/kaggle/input'): for filename in filenames: print(os.path.join(dirname, filename)) ​ # 读取数据 test_data = pd.read_csv("../input/titanic/test.csv") test_data.head() train_data = pd.read_csv("../input/titanic/train.csv") train_data.head() # 简要的数据查看，分析男女生存状况 women = train_data.loc[train_data.Sex == 'female']["Survived"] rate_women = sum(women)/len(women) print("% of women who survived:", rate_women)  men = train_data.loc[train_data.Sex == 'male']["Survived"] rate_men = sum(men)/len(men) print("% of men who survived:", rate_men) # 随机森林模型，选取4个特征 from sklearn.ensemble import RandomForestClassifier y = train_data["Survived"] features = ["Pclass", "Sex", "SibSp", "Parch"] X = pd.get_dummies(train_data[features])# get_dummies编码处理 X_test = pd.get_dummies(test_data[features]) # 设置模型参数 model = RandomForestClassifier(n_estimators=100, max_depth=5, random_state=1) model.fit(X, y)#训练 predictions = model.predict(X_test)#预测 # 输出预测文件 output = pd.DataFrame({'PassengerId': test_data.PassengerId, 'Survived': predictions}) # 写入csv文件 output.to_csv('my_submission.csv', index=False) print("Your submission was successfully saved!") 

• 保存、运行
  
  
  
  往下找到 output files
  
  

完成课程 Intro to Machine Learning，发了一张证书，哈哈，加油！