Preparing for version 1.0.4

CHANGELOG.md

@@ -4,6 +4,14 @@ All notable changes to this project will be documented in this file.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+## [1.0.4] - 2024-01-31
+
+### Added
+- Add a parameter to `artificial_ssl_dataset` to force a minimum of instances. Issue #11
+
+### Fixed
+- DeTriTraining now is vectorized and is faster than before.
+
 # [1.0.3.1] - 2023-04-01
 
 ### Changed

sslearn/__init__.py

@@ -1,4 +1,4 @@
-__version__='1.0.3.1'
+__version__='1.0.4'
 __AUTHOR__="José Luis Garrido-Labrador" # Author of the package
 __AUTHOR_EMAIL__="jlgarrido@ubu.es" # Author's email
 __URL__="https://pypi.org/project/sslearn/"

sslearn/wrapper/_co.py

@@ -1020,7 +1020,6 @@ def score(self, X, y, sample_weight=None):
 
  return self.ensemble_estimator.score(X, y, sample_weight)
 
-
 # Done and tested
 class CoForest(BaseCoTraining):
  def __init__(self, base_estimator=DecisionTreeClassifier(), n_estimators=7, threshold=0.75, bootstrap=True, n_jobs=None, random_state=None, version="1.0.3"):

test/test_model_selection.py

@@ -26,13 +26,13 @@ def test_artificial_ssl_dataset_with_force_minimum():
  X = np.concatenate((X, [X_0]), axis=0)
  y = np.concatenate((y, [y_0]), axis=0) 
 
- X, y, X_unlabel, true_label = artificial_ssl_dataset(X, y, label_rate=0.02, force_minimum=2)
+ X, y, X_unlabel, true_label = artificial_ssl_dataset(X, y, label_rate=0.02, force_minimum=1)
  assert X_unlabel.shape[0] == true_label.shape[0]
- assert X_unlabel.shape[0]/X.shape[0] == pytest.approx(0.96, abs=0.01)
- # Check if all labels have at least 10 instances
  for i in np.unique(y):
  assert np.sum(y == i) >= 1
 
+ pytest.raises(ValueError, artificial_ssl_dataset, X, y, label_rate=0.02, force_minimum=2)
+
 def test_StratifiedKFoldSS():
  X, y = load_iris(return_X_y=True)
  splits = 5