Problem: model.fit fails with numpy.core._exceptions._ArrayMemoryError: Unable to allocate 71.6 GiB for an array with shape (98000, 98000) and data type float64
catboost version: 1.2
Operating System:ubuntu

Partial Code:

import numpy as np
import catboost as cb
from sklearn.model_selection import GridSearchCV

grid = {"learning_rate": [0.01,0.03],
"depth": [4,6],
"iterations": [10],
}

cbr = cb.CatBoostRegressor(loss_function='RMSE',eval_metric="RMSE",boosting_type ='Plain')#,task_type='GPU')
gscv = GridSearchCV(estimator = cbr, param_grid = grid)#, cv = 3)#, n_jobs=-1)
gscv.fit(X_train, y_train, cat_features = categorical_features_indices)

Error:

0: learn: 1.5782847 total: 207ms remaining: 1.86s
1: learn: 1.5758104 total: 378ms remaining: 1.51s
2: learn: 1.5733945 total: 550ms remaining: 1.28s
3: learn: 1.5710246 total: 678ms remaining: 1.02s
4: learn: 1.5686950 total: 805ms remaining: 805ms
5: learn: 1.5663753 total: 932ms remaining: 622ms
6: learn: 1.5641121 total: 1.06s remaining: 453ms
7: learn: 1.5618219 total: 1.18s remaining: 296ms
8: learn: 1.5596248 total: 1.31s remaining: 146ms
9: learn: 1.5576024 total: 1.44s remaining: 0us
/opt/conda/anaconda/lib/python3.7/site-packages/sklearn/model_selection/_validation.py:774: UserWarning: Scoring failed. The score on this train-test partition for these parameters will be set to nan. Details:
Traceback (most recent call last):
File "/opt/conda/anaconda/lib/python3.7/site-packages/sklearn/model_selection/_validation.py", line 761, in _score
scores = scorer(estimator, X_test, y_test)
File "/opt/conda/anaconda/lib/python3.7/site-packages/sklearn/metrics/_scorer.py", line 418, in _passthrough_scorer
return estimator.score(*args, **kwargs)
File "/opt/conda/anaconda/lib/python3.7/site-packages/catboost/core.py", line 5856, in score
residual_sum_of_squares = np.sum((y - predictions) ** 2)
numpy.core._exceptions._ArrayMemoryError: Unable to allocate 71.6 GiB for an array with shape (98000, 98000) and data type float64