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.

1. Run All code in del_feature.ipynb to select important features and save in the numpy_selected_feature_5fold_original_300.npy file.

2. Run All code in sub_with_reg_and_cls_422 to classify product quality using the regression model and classification model.