class_docstr: Test class for output tests.
code: def make_learning_curve_data(self):
      # create a featureset with the digits data
      fs_digits, _ = make_digits_data(test_size=0)
  
      # Write this feature set to file
      train_path = train_dir / "test_learning_curve1.jsonlines"
      writer = NDJWriter(train_path, fs_digits)
      writer.write()
  
      # create featureset with all except the last feature called "pixel_7_7"
      fs_digits.filter(features="pixel_7_7", inverse=True)
  
      # Write this feature set to file
      train_path = train_dir / "test_learning_curve2.jsonlines"
      writer = NDJWriter(train_path, fs_digits)
      writer.write()
  
imports: import csv
  import json
  import re
  import unittest
  import warnings
  from ast import literal_eval
  from collections import defaultdict
  from itertools import chain, product
  from pathlib import Path
  from unittest.mock import Mock, patch
  import numpy
  import pandas
  from numpy.testing import assert_almost_equal, assert_array_almost_equal, assert_array_equal
  from sklearn.model_selection import ShuffleSplit, learning_curve
  from sklearn.naive_bayes import MultinomialNB
  from skll.data import FeatureSet, NDJReader, NDJWriter, Reader
  from skll.experiments import run_configuration
  from skll.experiments.output import _compute_ylimits_for_featureset
  from skll.learner import Learner
  from skll.utils.constants import VALID_TASKS
  from skll.utils.logging import close_and_remove_logger_handlers, get_skll_logger
  from skll.utils.testing import backward_compatibility_dir, config_dir, create_jsonlines_feature_files, fill_in_config_options, fill_in_config_paths, fill_in_config_paths_for_single_file, make_classification_data, make_digits_data, make_regression_data, other_dir, output_dir, remove_jsonlines_feature_files, test_dir, tests_dir, train_dir, unlink
label_desc: Use image node_id 4 for calling the TestOutput obj's underlying member method code with example usage: obj.make_learning_curve_data() without return types