code: def test_progress_1():
      lr = SoftmaxRegression(
          epochs=1,
          eta=0.005,
          minibatches=1,
          print_progress=1,
          random_seed=1,
      )
  
      lr.fit(X_bin, y_bin)
  
file_path: mlxtend/mlxtend/classifier/tests/test_softmax_regression.py
imports: import numpy
  from sklearn.base import clone
  from mlxtend.classifier import SoftmaxRegression
  from mlxtend.data import iris_data
  from mlxtend.utils import assert_raises
label_desc: Use image node_id 5 for calling a global function with example usage: test_progress_1() without return types