Machine learning approach of price prediction

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dc.contributor.authorJamkhandikar, Irfan
dc.contributor.authorMohammad Farhan, (19CO38)
dc.contributor.authorShaikh, Afsar Ahmed (19CO52)
dc.contributor.authorThokan, Naveed Naushad (19CO60)
dc.date.accessioned2023-06-12T05:37:57Z
dc.date.available2023-06-12T05:37:57Z
dc.date.issued2023-05
dc.description.abstractThis 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.identifier.urihttp://localhost:8080/xmlui/handle/123456789/4115
dc.language.isoenen_US
dc.publisherAIKTCen_US
dc.relation.ispartofseriesPE0739;
dc.subjectProject Report - COen_US
dc.titleMachine learning approach of price predictionen_US
dc.typeProject Reporten_US
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