# Adding 'Price' (target) column to the data boston.target.shape data['Price'] = boston.target data.head() data.describe() data.info() # Input Data x = boston.data # Output Data y = boston.target # splitting data to training and testing dataset. #from sklearn.cross_validation import...
kaggle-datasetames-housingregression-analysismultiple-linear-regressionames-housing-dataset UpdatedMar 5, 2020 R westurner/house_prices Star4 machine-learningscikit-learnkaggle-competitionautomltpotkaggle-house-pricesames-housing UpdatedDec 26, 2016
It reviewed the factors that affected housing prices in literature and used the dataset of the housing price in Beijing in Kaggle to study the factors affected the housing price in Beijing. The results showed that Google AutoML had the best performance in predicting housing prices in Beijing. It...
回答问题12.2:这个结果并不是理想的,应该还需要利用决策树的其他参数进行网格搜索,以及使用更多的特征; python机器学习 赞收藏 分享 阅读6.1k更新于2019-03-31 宇翔 0声望4粉丝 热爱生活,热爱科研 « 上一篇 下一篇 » 机器学习项目:构建垃圾邮件分类 ...
房屋价格预测 艾姆斯住房数据集摘自kaggle竞赛。 该项目的目的是预测Boston Housing Dataset中房屋的房价。 提供了两个文件,即训练和测试,并且要估计测试数据的价格。 在这里,我已使用XGBoost进行预测。 感谢Krish Naik制作了这些精彩的视频,以帮助他们理解和实施房价预测。 稍后,我将添加探索性数据分析,并将XGBoost模型...
# Adding 'Price' (target) column to the data boston.target.shape data['Price'] = boston.target data.head() data.describe() data.info() # Input Data x = boston.data # Output Data y = boston.target # splitting data to training and testing dataset. ...
Explore and run machine learning code with Kaggle Notebooks | Using data from Housing Price Dataset
Explore and run machine learning code with Kaggle Notebooks | Using data from Housing Price Dataset
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