HappyML is a machine learning library for educational purpose. This library simplified many aspects of machine learning including preprocessing, model creation, data visualization...etc. This library is for experimental purpose and does not recommend to use in production.
HappyML 是一個教學用的機器學習函式庫。該函式庫簡化了機器學習的程式碼寫作。包括：前處理、模型建置、資料視覺化...等方面。本函式庫乃教學用途，實驗性質重，可能存在不少潛在錯誤。不建議直接使用在正式場合。
如果您對每個版本修改了哪些東西的細節好奇，也歡迎您參考 ReleaseLog.txt。
- 2024/03/23-01
- [NEW] pytorch.py: The file contains a class called Sequential. The class inherits torch.nn.Module and provides functions that allow people who are only familiar with TensorFlow/Keras, but not PyTorch, to build PyTorch models using Keras-like functions in the class.
- 2023/02/10-01
- [BUGFIX] preprocessor.feature_scaling(): Fix an error message caused by the feature_scaling() function when the incoming array is not a DataFrame.
- [NEW] MultipleRegressor.named_features: It can return the dimension reduction result with "field name" except the column "const" instead of "index". For example: ['R&D Spend', 'Marketing Spend'].
- 2023/02/05-01
- [NEW] MultipleRegressor: Now it can automatically detect if there are constants in the incoming X_train and X_test. If not, it will be added automatically.
- 2021/06/06-01
- [FIX] Heatmap in criteria.AssumptionChecker.features_correlation() will overlap with other plot.
- 2021/06/03-01
- [FIX] cluster_drawer() shows error message: "findfont: Font family ['sans-serif'] not found. Falling back to DejaVu Sans"
- 2021/05/26-01
- [FIX] PCASelector.fit() shows same information no matter verbose=True or =False.
- 2021/05/19-01
- [REMOVE] Remove auto=False parameter from KBestSelector.fit()
- [FIX] KBestSelector.fit() show nothing when <>auto and verbose=True.
- [FIX] Remove iid= parameter from GridSearchCV()
- 2020/08/03-01
- [NEW] Add show_first_n_images() into model_drawer.py
- [NEW] Add create_seq_model() into neural_networks.py
- 2020/07/26-01
- [NEW] Add epochs_metrics_plot() into model_drawer.py
- 2020/07/26-01
- [NEW] Create this repository.