Model Diagnostics, Machine Learning.
name='XGB2_underfit') exp.model_diagnose(model="XGB2_underfit", show='accuracy_table') clf3 = XGB2Classifier(n_estimators=200, max_depth=2, eta = 0.05, reg_alpha = 0.2, reg_lambda = 0.2, max_bin = 256, feature_types = "numerical", random_state=0) exp.model_train(model=clf3, name='XGB2_tuned')