[DEFAULT]
shuffle = False
save_cv_folds = False
learning_curve_cv_folds_list = []
num_cv_folds = 10
test_file = 
random_folds = False
class_map = {}
grid_search_jobs = 0
log = 
train_file = 
featuresets = []
objectives = ['f1_score_micro']
min_feature_count = 1
objective = f1_score_micro
id_col = id
param_grids = []
hasher_features = 0
sampler = 
feature_scaling = none
fixed_parameters = []
predictions = 
custom_learner_path = 
suffix = 
sampler_parameters = []
featureset_names = []
ids_to_floats = False
results = 
cv_folds_file = 
grid_search = False
probability = False
label_col = y
test_directory = 
grid_search_folds = 3
models = 
pos_label_str = 
feature_hasher = False
train_directory = 
learning_curve_train_sizes = []

[General]
experiment_name = config_parsing
task = evaluate

[Input]
learners = ['LogisticRegression']
suffix = .jsonlines
custom_learner_path = ../other/majority_class_learner.py
train_file = ../train/f0.jsonlines
test_file = ../train/f1.jsonlines

[Tuning]
grid_search = true
objectives = ['accuracy']
objective = f1_score_micro

[Output]
probability = false
results = ../output
log = ../output

