Side by side cuML vs Sklearn

sidebyside.markdown

|  ######cuML######                 |  ######Sklearn######                 |
|                                   |                                      |
|  from cuml import                 |  from sklearn.ensemble import        |
|  RandomForestClassifier as cuRF   |  RandomForestClassifier as sklRF     |
|                                   |  import multiprocessing as mp        |
|                                   |                                      |
|  # cuml Random Forest params      |  #sklearn Random Forest params       |
|  cu_rf_params = {                 |  skl_rf_params = {                   |
|     ‘n_estimators’: 25,           |      ‘n_estimators’: 25,             |
|     ‘max_depth’: 13,              |      ‘max_depth’: 13,                |
|      ‘n_bins’: 15,                |                                      |
|      ‘n_streams’: 8 }             |      ‘n_jobs’: mp.cpu_count() }      |
|                                   |                                      |
|  cu_rf = cuRF(**cu_rf_params)     |  skl_rf = sklRF(**skl_rf_params)     |
|  cu_rf.fit(X_train, y_train)      |  skl_rf.fit(X_train, y_train)        |
|                                   |                                      |
|  print("cuml RF Accuracy Score: " |  print("sklearn RF Accuracy Score: " |
|  accuracy_score(                  |  accuracy_score(                     |
|  cu_rf.predict(X_test), y_test))  |  skl_rf.predict(X_test), y_test))    |