title: How to set the weight in muticlass (4 classes) classification in lightgbm for imbalanced dataset?
body: <p>I am trying to using lightgbm to classify a 4-classes problem. But the 4-classes are imbalanced and nearly 2000:1:1:1.</p>
  
  <p>In lightgbm, the params 'is_unbalance' and scale_pos_weight are just for binary classification.</p>
  
  <pre><code>params = {
      'objective':'multiclassova',
      'num_class':4,
      'is_unbalance':True,
      'metric': 'multi_logloss',
      'max_depth':2,
      'learning_rate':0.15,
      'feature_fraction':0.8,
      'bagging_fraction':0.8,
      'bagging_freq':4,
      'reg_alpha':5,
      'reg_lambda':3,
      'cat_smooth':0,
      'num_iterations':53, 
  }
  lgb_train = lgb.Dataset(X_train,Y_train, 
  categorical_feature=category_feature)
  gbm = lgb.train(params,lgb_train)
  </code></pre>