title: How to change LightGBM Parameters when it is running?
body: <p>So, I want to either change the parameter of LightGBM after it is running <code>or</code> After running 10000 times, I want to add another model with different parameters but use the previously trained model. </p>
  
  <p>Something like this:</p>
  
  <pre><code>params = {
          "objective" : "regression", 
          "metric" : "mae", 
          "num_leaves" : 35, 
          "learning_rate" : 0.05, 
          "bagging_fraction" : 0.7,
          "bagging_seed" : 0, 
          "num_threads" : 4,
          "colsample_bytree" : 0.7,
          'min_data_in_leaf':200, 
          'min_split_gain':0.0004,
          'lambda_l2':0.1
  }
  
  model = lgb.train(  params, 
                      train_set = train_set,
                      num_boost_round=1000,
                      early_stopping_rounds=200,
                      verbose_eval=100, 
                      valid_sets=[train_set,valid_set]
  )
  
  params = {
          "objective" : "dart", 
          "metric" : "mae", 
          "num_leaves" : 44, 
          "learning_rate" : 0.01, 
          "bagging_fraction" : 0.3,
          "bagging_seed" : 0, 
          "num_threads" : 4,
          "colsample_bytree" : 0.1,
          'min_data_in_leaf':400, 
          'min_split_gain':0.0001,
          'lambda_l2':0.2
  }
  
  model = lgb.train(                   
                      params, 
                      train_set = train_set,
                      num_boost_round=2000,
                      early_stopping_rounds=200,
                      verbose_eval=100,
                      init_model=model,          
                      valid_sets=[train_set,valid_set]
  
  )
  </code></pre>
  
  <p>But here, when i use <code>init_model=model</code>, I get thiserror:</p>
  
  <p><code>LightGBMError: Cannot set predictor after freed raw data, set free_raw_data=False when construct Dataset to avoid this.</code></p>