2ab1119596b420cc696a783271d617562ccf7e28,examples/plot_EEG_Example.py,,,#,123

Before Change

train, test = train_test_split(np.arange(len(eeg["classes"])), random_state=0)

rfc_param_grid = {"n_estimators": [8, 16, 32, 64, 128, 256, 512, 1024]}
model_cesium = build_model_from_featureset(fset_cesium.isel(name=train),
                                          RandomForestClassifier(max_features="auto",
                                                                 random_state=0),
                                          params_to_optimize=rfc_param_grid)

After Change

model_guo.fit(fset_guo.iloc[train], eeg["classes"][train])

model_dwt = KNeighborsClassifier(3)
model_dwt.fit(fset_dwt.iloc[train], eeg["classes"][train])

//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
// Prediction
// ----------

Instances