input: Write a python function to split a dataset into training and testing sets with specified features and target column.
  assert isinstance(split_dataset(data, ['text', 'subject'], 'label', 0.2), tuple)
  assert len(split_dataset(data, ['text', 'subject'], 'label', 0.2)) == 4
  assert split_dataset(data, ['text', 'subject'], 'label', 0.2)[0].shape[1] == 2
output: import pandas as pd
  from sklearn.model_selection import train_test_split
  
  def split_dataset(data, feature_columns, target_column, test_size):
      X = data[feature_columns]
      y = data[target_column]
      X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=test_size)
      return X_train, X_test, y_train, y_test