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Poster Session Ⅱ : Artificial Intelligence / IoT & Big Data

Ensemble-based Semi-supervised Learning to Improve sales prediction for medical products

초록

영어

Recently, due to the recent significant advances in machine learning and deep learning, it is being utilized in many fields. However, real-world data in the medical field significantly degrades the performance of machine learning algorithms due to problems that are heavily skewed to specific states or that the distribution of data is unbalanced. Therefore, this study solves the problem of not being learned by converting the dependent variable into a regression problem that predicts using a new dependent variable by pseudo labeling. Also, this study present ensemble methods to improve the performance of the model and prevent overfitting.

목차

Abstract
I. INTRODUCTION
II. PROPOSED METHOD
A. Dataset
B. Generating dependent variables with pseudo labeling
III. EXPERMIMENT
A. Experiment result with each model
B. Experiment result with Ensemble model
IV. CONCLUSION
REFERENCES

저자정보

  • Wook Lee School of Electrical Engineering Korea University
  • Junhee Seok School of Electrical Engineering Korea University

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