System for predicting house or residential properties prices using machine learning techniques, has machine learning model that identifies correlations between features and house prices, where model finds correlation between number of bedrooms and price
	ETHIRAJULU V; PAVA S P; REDDY A K P; BABU A P; PRIYADHARSHINI D R C
	2023-10-16
专利权人	BHARATH HIGHER EDUCATION & RES INST (BHAR-Non-standard)
申请日期	2023-10-16
专利号	IN202341069431-A
成果简介	NOVELTY - The system has a machine learning model that identifies correlations between features and house prices. The model finds a correlation between the number of bedrooms and the price, where the model's predictions are based on patterns learned from historical data. The accuracy of the predictions heavily depends on the quality and relevance of the data used for training the model. The model identifies important features based on the given dataset, where importance of features vary in different contexts or regions. USE - System for predicting house or residential properties prices using machine learning techniques. ADVANTAGE - The system can obtain accurate predictions, helping buyers, sellers, and real estate professionals navigate the housing market more effectively by leveraging historical data, preprocessing techniques, feature engineering, model training, evaluation, and optimization. The system improves model's accuracy and generalization ability.
IPC 分类号	G06K-009/62 ; G06N-020/00 ; G06N-003/08 ; G06N-005/00 ; G06Q-050/16
国家	印度
专业领域	信息技术
语种	英语
成果类型	专利
文献类型	科技成果
条目标识符	http://119.78.100.226:8889/handle/3KE4DYBR/19905
专题	中国科学院新疆生态与地理研究所
作者单位	BHARATH HIGHER EDUCATION & RES INST (BHAR-Non-standard)
推荐引用方式 GB/T 7714	ETHIRAJULU V,PAVA S P,REDDY A K P,et al. System for predicting house or residential properties prices using machine learning techniques, has machine learning model that identifies correlations between features and house prices, where model finds correlation between number of bedrooms and price. IN202341069431-A[P]. 2023.

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