• 제목/요약/키워드: random forest missing value imputation

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결측값 대체를 위한 데이터 재현 기법 비교 (Comparison of Data Reconstruction Methods for Missing Value Imputation)

  • 김청호;강기훈
    • 문화기술의 융합
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    • 제10권1호
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    • pp.603-608
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    • 2024
  • 무응답 및 결측값은 표본 탈락, 설문조사에 대한 답변 회피 등으로 발생하며 정보의 손실 및 편향된 추론의 가능성이 있는 문제가 발생하게 되며, 이 경우 결측값을 적절한 값으로 바꾸는 대체가 필요하게 된다. 본 논문에서는 결측값에 대한 대체 방법으로 제안되었던 평균 대체, 다중회귀 대체, 랜덤 포레스트 대체, K-최근접 이웃 대체, 그리고 딥러닝을 기본으로 한 오토인코더 대체와 잡음제거 오토인코더 대체 방법을 비교한다. 결측값을 대체하는 이러한 방법들에 대해 설명하고, 연속형의 모의실험 데이터와 실제 데이터에 접목시켜 각 방법들을 비교하였다. 비교 결과 대부분의 경우에서 다중 대체 방법인 랜덤 포레스트 대체 방법과 잡음제거 오토인코더 대체 방법의 성능이 좋았음을 확인하였다.

Household, personal, and financial determinants of surrender in Korean health insurance

  • Shim, Hyunoo;Min, Jung Yeun;Choi, Yang Ho
    • Communications for Statistical Applications and Methods
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    • 제28권5호
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    • pp.447-462
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    • 2021
  • In insurance, the surrender rate is an important variable that threatens the sustainability of insurers and determines the profitability of the contract. Unlike other actuarial assumptions that determine the cash flow of an insurance contract, however, it is characterized by endogenous variables such as people's economic, social, and subjective decisions. Therefore, a microscopic approach is required to identify and analyze the factors that determine the lapse rate. Specifically, micro-level characteristics including the individual, demographic, microeconomic, and household characteristics of policyholders are necessary for the analysis. In this study, we select panel survey data of Korean Retirement Income Study (KReIS) with many diverse dimensions to determine which variables have a decisive effect on the lapse and apply the lasso regularized regression model to analyze it empirically. As the data contain many missing values, they are imputed using the random forest method. Among the household variables, we find that the non-existence of old dependents, the existence of young dependents, and employed family members increase the surrender rate. Among the individual variables, divorce, non-urban residential areas, apartment type of housing, non-ownership of homes, and bad relationship with siblings increase the lapse rate. Finally, among the financial variables, low income, low expenditure, the existence of children that incur child care expenditure, not expecting to bequest from spouse, not holding public health insurance, and expecting to benefit from a retirement pension increase the lapse rate. Some of these findings are consistent with those in the literature.