Projects Aims to compare the accuracy of different machine learning algorithms. for that we use the information customers leave in the form of the trace of browsing history data or user information when they visit an online shopping site. on this information we apply different machine learning algorithms to predict online shoppers purchasing intention and based on that prediction we compared the accuracy of different machine learning algorithms.
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a research project analyzing machine learning models for predicting customer behavior in e-commerce. Through the comparison of clickstream and customer data, the study identified Random Forest as the most effective algorithm for purchase prediction.
sundram10/Online-Shopper-Purchasing-Intention-Prediction
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a research project analyzing machine learning models for predicting customer behavior in e-commerce. Through the comparison of clickstream and customer data, the study identified Random Forest as the most effective algorithm for purchase prediction.
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