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Industrial Problem Solution

A Study on the Possibility of Explanation and Analysis of Prediction System Using Machine Learning Method

2020-06-15

1. Company introduction

IntelliCode Co., Ltd. is a system solution provider that uses log data from computer systems to detect anomalies.


2. Problem Background and Summary

A study of methodology that enables humans to understand and interpret patterns found by machines in machine learning models.



3. Solving Process

Certain methods, such as regression analysis and decision tree learning methods, have some potential for interpretation of the learning process or learning result itself due to the nature of the model.

Provides a deion of the interpretability of the above model and examples of its application

In case of artificial neural networks such as deep learning, the internal process of learning makes it difficult to obtain interpretability through the model itself and the learning process.

Provides a deion and application example of the model-agnostic method of permutation feature import and local interoperable model-organization (LIME) among model-specific methods that are applicable regardless of model



4. Ripple effects and future plans

Visualization and UX implementation will be used for practical use.

A joint study on the analysis and implementation of the relevant latest paper, which continues to be published, will be conducted.

1. Company introduction

IntelliCode Co., Ltd. is a system solution provider that uses log data from computer systems to detect anomalies.


2. Problem Background and Summary

A study of methodology that enables humans to understand and interpret patterns found by machines in machine learning models.



3. Solving Process

Certain methods, such as regression analysis and decision tree learning methods, have some potential for interpretation of the learning process or learning result itself due to the nature of the model.

Provides a deion of the interpretability of the above model and examples of its application

In case of artificial neural networks such as deep learning, the internal process of learning makes it difficult to obtain interpretability through the model itself and the learning process.

Provides a deion and application example of the model-agnostic method of permutation feature import and local interoperable model-organization (LIME) among model-specific methods that are applicable regardless of model



4. Ripple effects and future plans

Visualization and UX implementation will be used for practical use.

A joint study on the analysis and implementation of the relevant latest paper, which continues to be published, will be conducted.