Table 1.
E-Commerce user purchase prediction experiment parameters.
Fig 1.
User collection heat related.
Table 2.
Dataset 1: The relationship between whether a user collects it or not.
Fig 2.
Dataset 2: The relationship between whether a user collects it or not.
Fig 3.
Accuracy of whether the user has collected it or not.
Fig 4.
Loss of whether the user has collected it or not.
Fig 5.
ROC of whether the user has collected it or not.
Fig 6.
Heatmap related to user adds to the shopping cart.
Fig 7.
Dataset 1: The relationship between whether a product is added to the shopping cart or not.
Table 3.
Dataset 2: The relationship between whether a product is added to the shopping cart or not.
Fig 8.
Accuracy of whether the user adds to the shopping cart.
Fig 9.
Loss of whether the user adds to the shopping cart.
Fig 10.
OC of whether the user adds to the shopping cart.
Fig 11.
Heat map related to user purchases.
Table 4.
Dataset 1: The purchasing numbers.
Fig 12.
Dataset 2: The relationship between purchasing or not.
Fig 13.
Accuracy of predicting user purchases.
Fig 14.
Loss in predicting user purchases.
Fig 15.
ROC for predicting user purchases.