Table 6 Configuration of algorithms adopted in each datasets
From: Unlocking teachers’ potential: MOOCLS, a visualization tool for enhancing MOOC teaching
Model | Hyper-parameters | Datasets | |||
|---|---|---|---|---|---|
A/R | S/I | V/V | S/G | ||
DT | Max_depth | 8 | 7 | 8 | 7 |
Criterion | Entropy | Entropy | Entropy | Entropy | |
Max_features | None | None | None | None | |
RF | N_estimator | 7 | 10 | 7 | 7 |
Max_depth | 8 | 7 | 8 | 8 | |
KNN | N_neighbors | 50 | 50 | 50 | 50 |
Leaf_size | 1 | 1 | 1 | 1 | |
Algorithm | Auto | Auto | Ball_tree | Auto | |
NN | Hidden_layer_size | 7 | 7 | 8 | 8 |
Max_iter | 500 | 500 | 500 | 500 | |