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| import time | |
| import xgboost as xgb | |
| from sklearn.model_selection import RandomizedSearchCV | |
| x_train, y_train, x_valid, y_valid, x_test, y_test = # load datasets | |
| clf = xgb.XGBClassifier() | |
| param_grid = { |
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| import numpy as np | |
| from scipy.sparse import csr_matrix | |
| def save_dataset(filename, x, y): | |
| np.savez(filename, data=x.data, indices=x.indices, | |
| indptr=x.indptr, shape=x.shape, target=y) | |
| def load_dataset(filename): |