9786200080967 - Regression Based Prediction of House Prices using Python di Rao N. V., Krishna; Laxmi B., Dhana (8 risultati)

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Taschenbuch. Condizione: Neu. Regression Based Prediction of House Prices using Python | Krishna Rao N. V. (u. a.) | Taschenbuch | 72 S. | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9786200080967 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 72 pp. Englisch.

Condizione: New. Print on Demand.

Condizione: New. PRINT ON DEMAND.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: 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.

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 72 pp. Englisch.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.