AI solution that Classifies the Product Quality
Presentation : LG-Presentation-KR.pdf
Jaeyoon Jung, Leader | Hannah Yun | Jiyul Ham |
┖ figures
┖ ~
┖ dataset
┖ data ~
┖ del_feature.ipynb
┖ sub_with_reg_and_cls_422.ipynb
┖ numpy_selected_feature_5fold_original_300.npy
del_feature.ipynb
- Feature Selection using SHAP value for train fitted classification model
numpy_selected_feature_5fold_original_300.npy
- numpy array that contains the information of Selected Feature from
del_feature.ipynb
sub_with_reg_and_cls_422.ipynb
- Train and Test the classification and regression model
We train and evaluate our model using the dataset from Classifying Smart Factory Product Quality Status
we assume that you have downloaded it and placed based on File Structure, inside the dataset folder.
-
Run All code in
del_feature.ipynb
to select important features and save in thenumpy_selected_feature_5fold_original_300.npy
file. -
Run All code in
sub_with_reg_and_cls_422
to classify product quality using the regression model and classification model.