Regression Based Prediction of House Prices using Python

von Rao N. V., Krishna
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Rao N. V., Krishna Regression Based Prediction of House Prices using Python
Rao N. V., Krishna - Regression Based Prediction of House Prices using Python

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Beschreibung

Regression is a measure of the relation between the mean value of one variable and corresponding values of other variables. In statistical modeling, regression analysis is a set of statistical processes for estimating the relationships among variables. The multiple linear regression explains the relationship between one continuous dependent variable (y) and two or more independent variables (x1, x2, x3... etc).This project uses multiple linear regression for estimating house price based on area in square feet and number of bed rooms. This project creates the needed GUI (Graphical User Interfaces) by using PyQt tool. PyUIC tool is used for automated generation of the code. This project is implemented through three modules: Data entry module, is used to provide the needed data to the project. The Analysis module is used to analyze and predict the house prices, based on the customer needs. The Front end module is used to create the needed GUI screens for the project. This Project uses PyQt tool to create the needed Graphical User Interfaces. PyQt is a Python binding of the cross-platform GUI toolkit Qt, implemented as a Python plug-in.

Mitwirkende

Autor:
Rao N. V., Krishna
Laxmi B., Dhana

Weitere Informationen

Biografie:
Rao N. V., Krishna
-Mr.N.V.Krishna Rao Assistant Professor of Department of CSE working at Institute of Aeronautical Engineering College,Hyderabad.He has vast experience in teaching C and Data Structures. -Ms.B.Dhanalaxmi is working as Assistant Professor at IARE in Information Technology Department. She has research experience in Data Mining and Big Data Analytics.
Sprache:
Englisch
Seitenanzahl:
72
Medientyp:
Taschenbuch
Verlag:
LAP Lambert Academic Publishing

Stammdaten

Produkttyp:
Taschenbuch
Veröffentlichungsdatum:
31. Mai 2019
Verpackungsabmessungen:
0.22 x 0.15 x 0.004 m;
GTIN:
09786200080967
DUIN:
C6LFD5OHHCT
CHF 40.55
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