Machine learning approach of price prediction

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dc.contributor.author Jamkhandikar, Irfan
dc.contributor.author Mohammad Farhan, (19CO38)
dc.contributor.author Shaikh, Afsar Ahmed (19CO52)
dc.contributor.author Thokan, Naveed Naushad (19CO60)
dc.date.accessioned 2023-06-12T05:37:57Z
dc.date.available 2023-06-12T05:37:57Z
dc.date.issued 2023-05
dc.identifier.uri http://localhost:8080/xmlui/handle/123456789/4115
dc.description.abstract This paper presents a Laptop price prediction system by using the supervised machine learning technique. The research uses multiple linear regression as the machine learning prediction method which offered 85% prediction precision. Using multiple linear regression, there are multiple independent variables but one and only one dependent variable whose actual and predicted values are compared to find precision of results. This paper proposes a system where price is dependent variable which is predicted, and this price is derived from factors like Laptop’s model, RAM, ROM (HDD or SSD), GPU, CPU, IPS Display, and Touch Screen. Price prediction is a useful feature forconsumers as well as businesses. A price prediction tool motivates users to engage with a brand or evaluate offers in order to spend their money wisely. Price prediction enables businesses to set pricing in a manner that builds customer engagement and loyalty. With Machine Learning (ML) technology a price prediction problem is formulated as a regression analysis which is a statistical technique used to estimate the relationship between a dependent/target variable and single or multiple independent (interdependent) variables. In regression, the target variable is numeric. This project will focus on ML algorithm used for price prediction. en_US
dc.language.iso en en_US
dc.publisher AIKTC en_US
dc.relation.ispartofseries PE0739;
dc.subject Project Report - CO en_US
dc.title Machine learning approach of price prediction en_US
dc.type Project Report en_US


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