Data link:https://www.kaggle.com/c/titanic/data a. Understanding data #导入数据包fromsklearnimportsvmimportpandasaspdimportnumpyasnu#将下载后的数据集进行数据训练importosos.chdir(r'E:\Titanic\titanic')#训练数据集train=pd.read_
Catalog:1.导数据/导包 2.查看缺失数据信息,填充缺失值 3.对7个数据分类:one-hot编码--按表头顺序--重点占比50% 4.特征选择 5.构建模型--训练数据集和测试数据集 6.选择算法 7.预测生成结果,提交kaggle机器学…
则返回true,否则返回false ageIsNull = pd.isnull(age...;***") # 如何取确定位置上的一个数据 行号+列名 row_index_83_age = titanic_survival.loc[83," 数据科学工程师面试宝典系列之二---Python机器kaggle案例:泰坦尼克号船员获救预测 1.Python机器学习kaggle案例 Numpy-python科学库;Pandas-python...
Kaggle · Getting Started Prediction Competition · Ongoing Join Competition more_horiz Titanic - Machine Learning from Disaster Start here! Predict survival on the Titanic and get familiar with ML basicsOverviewDataCodeModelsDiscussionLeaderboardRules...
Titanic Survival Prediction Project This project uses the Titanic dataset to predict whether a passenger survived or not based on various features such as age, gender, fare, class, and titles derived from names. The goal is to apply feature engineering and train multiple classification models to ...
Titanic Survival Prediction App A web application that predicts how likely you would have survived the Titanic disaster based on various features. This app uses a machine learning model to make predictions and visualizes the results using t-SNE plots. Features Predict survival likelihood based on us...
35.4s 30 /opt/conda/lib/python3.7/site-packages/traitlets/traitlets.py:2935: FutureWarning: --Exporter.preprocessors=["remove_papermill_header.RemovePapermillHeader"] for containers is deprecated in traitlets 5.0. You can pass `--Exporter.preprocessors item` ... multiple times to add items to a...
Explore and run machine learning code with Kaggle Notebooks | Using data from Titanic - Machine Learning from Disaster
The Titanic challenge hosted by Kaggle is a competition in which the goal is to predict the survival or the death of a given passenger based on a set of variables describing him such as his age, his sex, or his passenger class on the boat. I have been playing with the Titanic dataset...
sns.set_style("whitegrid") sns.plt.plot(roc_survival[0], roc_survival[1]) sns.plt.show() Logistic Regression using Scikit-Learn Here we shall learn how to perform modeling using sci-kit-learn: from sklearn import metrics from sklearn.linear_model import LogisticRegression log_sci_model ...