In this paper, 40 features, available in dataset of houses, are taken from Kaggle platform and have been considered for prediction of house prices. The data of six different cities of India has been included, and these are Delhi, Bangalore, Hyderabad, Kolkata, Mumbai, and Chennai. Here, we...
The majority of houses in the dataset have 2.5 bathrooms. Similar to the bedrooms, a higher number of bathrooms tends to increase the house price. However, houses with 0 and 7.5 bathrooms are anomalies. During deep exploration, I identified that these houses have impractical layouts, which affec...
Developed advanced regression models to predict house prices using the Ames Housing dataset. Achieved a grade of 90% under Prof. Vered Aharonson and ranked 550th in the Kaggle competition. - NatanGrayman/Boston-Housing-Prices-Regression
With limited dataset and data features, a practical and composite data pre-processing, creative feature engineering method is examined in this paper. The paper also proposes a hybrid Lasso and Gradient boosting regression model to predict individual house price. The proposed approach has recently been...
李沐动手学深度学习课程所用的02_DataSet_Kaggle_House,可以提前下载下来放进目录中,别因为网络原因耽误代码实现!!点赞(0) 踩踩(0) 反馈 所需:1 积分 电信网络下载 基于Matlab界面的口罩识别预警[Matlab界面] .zip 2024-12-21 20:30:23 积分:1 基于Matlab界面的卡尔曼小球运动跟踪[Matlab界面] .zip ...
In addition to these data, we validated our algorithm on the KAGGLE house dataset, which covers a wide range of features. The results of the hybrid algorithm were compared using multiple linear regression, Lasso, ridge regression, Support Vector Regression (SVR), AdaBoost, decision tree, random...
Data-driven pricing, in theory, will result in lower resource use on the part of the agents, and thus, a quicker (and more lucrative) sale. 3. Data Sourcing Our analysis will focus on the Ames, Iowa Housing Dataset compiled by Dean De Cock in 2011. This dataset includes 79 explan...
Something went wrong and this page crashed! If the issue persists, it's likely a problem on our side. Unexpected end of JSON input SyntaxError: Unexpected end of JSON input
Explore and run machine learning code with Kaggle Notebooks | Using data from House Prices - Advanced Regression Techniques
(missing: https://www.kaggle.com/static/assets/6084.f4312d5ceab69cdedec9.js) at r.f.j (https://www.kaggle.com/static/assets/runtime.js?v=dc5e9e2d37e9ce537d83:1:10505) at https://www.kaggle.com/static/assets/runtime.js?v=dc5e9e2d37e9ce537d83:1:1295 at Array.reduce (<...