# Define Search Param
search_params = {
                 'n_components': [5, 6, 7, 8]
                 ‘learning_method’: [‘online’,’batch’],
                 ‘learning_decay’: [0.5, 0.7, 0.9],
                 ‘learning_offset’: [1, 5, 10]
                }

# Init the Model
lda = LDA(random_state = 123)

# Init Grid Search Class
model = GridSearchCV(lda, param_grid = search_params)

# Do the Grid Search
model.fit(sessions_vectorized)

#Pick the best model
best_lda_model = model.best_estimator_
best_lda_model.fit(sessions_vectorized)