Prediction of Real Estate Price Using Clustering Techniques

被引:1
|
作者
Pradeepthi, C. [1 ]
Geetha, V. J. Vijaya [1 ]
Ramasubbareddy, Somula [2 ]
Govinda, K. [3 ]
机构
[1] SPMVV Univ, SOET, Tirupati, Andhra Pradesh, India
[2] VNRVJIET, Informat Techgnol, Nizampet Rd, Hyderabad, Telangana, India
[3] VIT Univ, SCOPE Sch, Vellore, Tamil Nadu, India
关键词
Prediction; K-means; DBSCAN; Density-based clustering; Farthest first clustering; PROMOTION;
D O I
10.1007/978-981-15-0135-7_27
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A standout among the most difficult assignments continuously condition is the expectation of house sales. Understanding the different components that impacts house sales is as much as critical on knowing a technique on the most proficient method to play out the forecast. Henceforth, it is a most extreme important to distinguish the relationship among various properties utilized in the dataset. These datasets can be received from different open databases and information repositories. Even though it has two distinct models (predictive and descriptive) for extracting the data, utilized grouping strategy for existing model, the support for utilizing such technique is clarified in this segment. With respect to the above expressed fundamental facts in this article, we play out the expectation.
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页码:281 / 289
页数:9
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