2024 ML Team Project _ Team 09

File description

Key Files

ClosedWorld.ipynb
Data Preprocessing and Model(SVM and RandomForest) for Experiments in a Closed-World Environment(Multi-Class Classification)

OpenWorld.ipynb
Data Preprocessing and Model (SVM or RandomForest) for Experiments in an Open-World Environment (Binary Classification | Multi-Class Classification)

s_final_categorical.ipynb
Modify final_categorical.ipynb to improve accuracy and conduct experiments with SVM and Random Forest model

Other Files

final_categorical.ipynb
Implementation of Open-World SVM/Random Forest and Closed-World Random Forest Models

feature_test.ipynb
Selecting Valid Metrics by Applying Them to the Actual Model

categorical_feature.ipynb
Feature Creation and Visualization for Extraction Verification

24-2 ML finding.pdf
A File Summarizing Findings

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Instructions

1. Add Data

• Download the following four data files and place them in the folder:
  • X3_mon_data.pkl, X4_mon_data.pkl (Extract from X3_X4_mon_data.zip)
  • mon_standard.pkl, unmon_standard10.pkl

2. Set Data Path

• For OpenWorld.ipynb and ClosedWorld.ipynb, enter the path where the data files are located into the path variable under the "Preparation" section at the top of the file.
• For s_final_categorical.ipynb, check the # File Path Setup section and enter the path into the path variable.

3. Run

• Execute the script as instructed.