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Fig 1.

2015.12-2020.3 scale of internet users in China.

(a) 2015.12-2020.3 online shopping user scale and utilization rate. (b) 2015.12-2020.3 mobile online shopping user scale and utilization rate.

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Fig 2.

The framework of the multi-graining scanning.

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Fig 3.

The framework of the cascade forest structure.

Each cascade level consists of two random forests and two completely random forests.

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Fig 4.

The framework of the improved deep forest.

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Table 1.

The first five rows of item information data.

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Table 2.

The first five rows of user information data.

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Fig 5.

Daily user behavior data change graph.

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Table 3.

Perdictive features of repurchase behavior of E—Commerce consumer.

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Table 4.

Perdictive model parameter settings.

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Table 5.

The cascade layer of improved deep forest parameters settings.

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Fig 6.

Comparison results under the different number of features.

(a) Accuracy comparison chart. (b) AUC comparison chart. (c) FI-value comparison chart.

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Table 6.

Performance comparison of predictive models.

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Fig 7.

Performance comparison of predictive models.

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Fig 8.

Comparison of training time between deep forest and CNN.

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