• 제목/요약/키워드: predictive accuracy

검색결과 797건 처리시간 0.03초

DR-LSTM: Dimension reduction based deep learning approach to predict stock price

  • Ah-ram Lee;Jae Youn Ahn;Ji Eun Choi;Kyongwon Kim
    • Communications for Statistical Applications and Methods
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    • 제31권2호
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    • pp.213-234
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    • 2024
  • In recent decades, increasing research attention has been directed toward predicting the price of stocks in financial markets using deep learning methods. For instance, recurrent neural network (RNN) is known to be competitive for datasets with time-series data. Long short term memory (LSTM) further improves RNN by providing an alternative approach to the gradient loss problem. LSTM has its own advantage in predictive accuracy by retaining memory for a longer time. In this paper, we combine both supervised and unsupervised dimension reduction methods with LSTM to enhance the forecasting performance and refer to this as a dimension reduction based LSTM (DR-LSTM) approach. For a supervised dimension reduction method, we use methods such as sliced inverse regression (SIR), sparse SIR, and kernel SIR. Furthermore, principal component analysis (PCA), sparse PCA, and kernel PCA are used as unsupervised dimension reduction methods. Using datasets of real stock market index (S&P 500, STOXX Europe 600, and KOSPI), we present a comparative study on predictive accuracy between six DR-LSTM methods and time series modeling.

행정 빅데이터 환경에서 컷오프-투표 분류기를 활용한 빅데이터 예측모형의 실험 (Operation Plan of Big Data Prediction Model using Cut-off-Voting Classifier in Administrative Big Data Environment)

  • 이우식
    • 문화기술의 융합
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    • 제10권3호
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    • pp.145-154
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    • 2024
  • 행정 빅데이터를 활용하는 예측 모형을 운영하기 위해서는 정책의 변화 및 변동성 심한 데이터의 특성이 고려가 되어야만 한다. 이런 상황을 고려하여 본 연구에서는 Cut-off Voting Classifier(CVC) 알고리즘을 제안한다. 제안하는 알고리즘은 여러개의 약 분류기를 활용하여 적중률이 급격하게 하락하는 것을 방지하는 알고리즘이다. 본 연구에서는 제안하는 알고리즘을 실험을 통해 성능을 검증한다. 성능검증 결과 급격하게 예측모형 적중률이 하락하는 상황에서도 안정적으로 예측률을 유지한다는 것을 입증할 수 있었다.

Seismic risk priority classification of reinforced concrete buildings based on a predictive model

  • Isil Sanri Karapinar;Ayse E. Ozsoy Ozbay;Emin Ciftci
    • Structural Engineering and Mechanics
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    • 제91권3호
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    • pp.279-289
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    • 2024
  • The purpose of this study is to represent a useful alternative for the preliminary seismic vulnerability assessment of existing reinforced concrete buildings by introducing a statistical approach employing the binary logistic regression technique. Two different predictive statistical models, namely full and reduced models, were generated utilizing building characteristics obtained from the damage database compiled after 1999 Düzce earthquake. Among the inspected building parameters, number of stories, overhang ratio, priority index, soft story index, normalized redundancy ratio and normalized lateral stiffness index were specifically selected as the predictor variables for vulnerability classification. As a result, normalized redundancy ratio and soft story index were identified as the most significant predictors affecting seismic vulnerability in terms of life safety performance level. In conclusion, it is revealed that both models are capable of classifying the set of buildings being severely damaged or collapsed with a balanced accuracy of 73%, hence, both are able to filter out high-priority buildings for life safety performance assessment. Thus, in this study, having the same high accuracy as the full model, the reduced model using fewer predictors is proposed as a simple and viable classifier for determining life safety levels of reinforced concrete buildings in the preliminary seismic risk assessment.

Accuracy of Magnetic Resonance Imaging in Pretreatment Lymph Node Assessment for Gynecological Malignancies

  • Sufian, Saira Naz;Masroor, Imrana;Mirza, Waseem;Hussain, Zainab;Hafeez, Saima;Sajjad, Zafar
    • Asian Pacific Journal of Cancer Prevention
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    • 제15권11호
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    • pp.4705-4709
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    • 2014
  • Objective: To determine the accuracy of magnetic resonance imaging (MRI) in detection of metastasis in pelvic and para-aortic lymph nodes from different gynecological malignancies. Materials and Methods: This retrospective cross sectional analytic study was conducted at the Department of Diagnostic Radiology, Aga Khan University Hospital Karachi Pakistan from January 2011 to December 2012. A sample of 48 women, age range between 20-79 years, fulfilling inclusion criteria were included. All patients had histopathologically proven gynecological malignancies in the cervix, endometrium or ovary and presented for a pretreatment MRI to our radiology department. Results: MRI was 100% sensitive and had a 100% positive predictive value to detect lymph node metastasis in lymph nodes with spiculated margins and 100% sensitive with a 75% positive predictive value to detect lymph node metastasis in a lymph node with lobulated margins. The sensitivity and positive predictive value of MRI to detect heterogeneous nodal enhancement were 100% and 75% respectively. Conclusions: Our study results reinforce that MRI should be used as a modality of choice in the pretreatment assessment of lymph nodes in proven gynaecological malignancies in order to determine the line of patientmanagement, distinguishing surgical from non-surgical cases.

Prediction Model for the Risk of Scapular Winging in Young Women Based on the Decision Tree

  • Gwak, Gyeong-tae;Ahn, Sun-hee;Kim, Jun-hee;Weon, Young-soo;Kwon, Oh-yun
    • 한국전문물리치료학회지
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    • 제27권2호
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    • pp.140-148
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    • 2020
  • Background: Scapular winging (SW) could be caused by tightness or weakness of the periscapular muscles. Although data mining techniques are useful in classifying or predicting risk of musculoskeletal disorder, predictive models for risk of musculoskeletal disorder using the results of clinical test or quantitative data are scarce. Objects: This study aimed to (1) investigate the difference between young women with and without SW, (2) establish a predictive model for presence of SW, and (3) determine the cutoff value of each variable for predicting the risk of SW using the decision tree method. Methods: Fifty young female subjects participated in this study. To classify the presence of SW as the outcome variable, scapular protractor strength, elbow flexor strength, shoulder internal rotation, and whether the scapula is in the dominant or nondominant side were determined. Results: The classification tree selected scapular protractor strength, shoulder internal rotation range of motion, and whether the scapula is in the dominant or nondominant side as predictor variables. The classification tree model correctly classified 78.79% (p = 0.02) of the training data set. The accuracy obtained by the classification tree on the test data set was 82.35% (p = 0.04). Conclusion: The classification tree showed acceptable accuracy (82.35%) and high specificity (95.65%) but low sensitivity (54.55%). Based on the predictive model in this study, we suggested that 20% of body weight in scapular protractor strength is a meaningful cutoff value for presence of SW.

RCP 기후변화 시나리오에 따른 우리나라 구상나무 잠재 분포 변화 예측 (Projecting the Potential Distribution of Abies koreana in Korea Under the Climate Change Based on RCP Scenarios)

  • 구경아;김재욱;공우석;정휘철;김근한
    • 한국환경복원기술학회지
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    • 제19권6호
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    • pp.19-30
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    • 2016
  • The projection of climate-related range shift is critical information for conservation planning of Korean fir (Abies koreana E. H. Wilson). We first modeled the distribution of Korean fir under current climate condition using five single-model species distribution models (SDMs) and the pre-evaluation weighted ensemble method and then predicted the distributions under future climate conditions projected with HadGEM2-AO under four $CO_2$ emission scenarios, the Representative Concentration Pathways (RCP) 2.6, 4.5, 6.0 and 8.5. We also investigated the predictive uncertainty stemming from five individual algorithms and four $CO_2$ emission scenarios for better interpretation of SDM projections. Five individual algorithms were Generalized linear model (GLM), Generalized additive model (GAM), Multivariate adaptive regression splines (MARS), Generalized boosted model (GBM) and Random forest (RF). The results showed high variations of model performances among individual SDMs and the wide range of diverging predictions of future distributions of Korean fir in response to RCPs. The ensemble model presented the highest predictive accuracy (TSS = 0.97, AUC = 0.99) and predicted that the climate habitat suitability of Korean fir would increase under climate changes. Accordingly, the fir distribution could expand under future climate conditions. Increasing precipitation may account for increases in the distribution of Korean fir. Increasing precipitation compensates the negative effects of increasing temperature. However, the future distribution of Korean fir is also affected by other ecological processes, such as interactions with co-existing species, adaptation and dispersal limitation, and other environmental factors, such as extreme weather events and land-use changes. Therefore, we need further ecological research and to develop mechanistic and process-based distribution models for improving the predictive accuracy.

능동전력필터의 기준신호발생을 위한 개선된 적응예측필터의 성능 분석 (Performance Analysis of Improved Adaptive Predictive Filter to Generate Reference Signal in Active Power Filter)

  • 배병열;백승택;한병문
    • 전력전자학회논문지
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    • 제9권6호
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    • pp.592-601
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    • 2004
  • 능동전력필터의 성능은 인버터의 특성, 제어 방법, 그리고 기준신호발생기의 정확도에 좌우된다. 이중에서 기준신호발생기의 정확도는 능동전력필터의 성능을 결정짓는 가장 중요한 요소이다. 본 논문은 개선된 적응예측필터로 구성한 새로운 기준신호발생기에 대해 소개하고 그 성능을 MATLAB을 이용한 시뮬레이션으로 검증하였다. 그리고 실제 하드웨어의 적용타당성을 평가하기 위해 개선된 기준신호발생기로 구성한 알고리즘을 TMS320C31 DSP(digital signal processor)에 구현하고 이 기준신호발생기를 기반으로 하는 단상능동전력필터의 축소모형을 제작하여 실험을 실시하였다. 시뮬레이션과 실험결과로 제안하는 기준신호발생기가 위상지연이 없는 기준신호를 추출하여 능동전력필터에 활용가능하며 그 성능도 대단히 우수함을 알 수 있었다.

출구조사의 체계적인 예측 편향에 대한 분석: 2010년 지방선거 출구조사를 중심으로 (Systematic Forecasting Bias of Exit Poll: Analysis of Exit Poll for 2010 Local Elections)

  • 김영원;최윤정
    • 한국조사연구학회지:조사연구
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    • 제12권3호
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    • pp.25-48
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    • 2011
  • 본 연구에서는 선거 출구조사에서 발생하는 편향을 분석하기 위해, 먼저 2010년 전국동시지방선거 출구조사의 표본설계와 표본추출오차, 그리고 무응답 현황 및 예측오차 등을 살펴보고, 이를 토대로 출구조사에서 체계적으로 발생하는 지역별 편향 문제를 다루었다. 출구조사에서 발생하는 편향을 통계적으로 검증하기 위해 Martin et al.(2005)이 제안한 예측 정확성 척도인 통계량 A를 사용하였다. 2010년 지방선거를 포함해 2006년 지방선거와 2007년 대통령 선거 방송사 출구조사 자료를 토대로 시 도 단위에서 지역별 편향을 분석해 본 결과, 여당 성향이 강한 지역에서는 여당 후보를 과대 추정하는 편향이 체계적으로 발생하고 있으며, 여당 성향이 강해질수록 이런 편향이 더 강해진다는 것을 확인할 수 있었다. 이런 연구결과는 향후 출구조사의 정확성 제고를 위한 방안을 모색하는 데 크게 기여할 수 있을 것으로 기대된다.

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Prediction of Chemotherapeutic Response in Unresectable Non-small-cell Lung Cancer (NSCLC) Patients by 3-(4,5-Dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium (MTS) Assay

  • Chen, Juan;Cheng, Guo-Hua;Chen, Li-Pai;Pang, Ting-Yuan;Wang, Xiao-Le
    • Asian Pacific Journal of Cancer Prevention
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    • 제14권5호
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    • pp.3057-3062
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    • 2013
  • Background: Selecting chemotherapy regimens guided by chemosensitivity tests can provide individualized therapies for cancer patients. The 3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2Htetrazolium, inner salt (MTS) assay is one in vitro assay which has become widely used to evaluate the sensitivity to anticancer agents. The aim of this study was to evaluate the clinical applicability and accuracy of MTS assay for predicting chemotherapeutic response in unresectable NSCLC patients. Methods: Cancer cells were isolated from malignant pleural effusions of patients by density gradient centrifugation, and their sensitivity to eight chemotherapeutic agents was examined by MTS assay and compared with clinical response. Results: A total of 37 patients participated in this study, and MTS assay produced results successfully in 34 patients (91.9%). The sensitivity rates ranged from 8.8% to 88.2%. Twenty-four of 34 patients who received chemotherapy were evaluated for in vitro-in vivo response analysis. The correlation between in vitro chemosensitivity result and in vivo response was highly significant (P=0.003), and the total predictive accuracy, sensitivity, specificity, positive predictive value, and negative predictive value for MTS assay were 87.5%, 94.1%, 71.4%, 88.9%, and 83.3%, respectively. The in vitro sensitivity for CDDP also showed a significant correlation with in vivo response (P=0.018, r=0.522). Conclusion: MTS assay is a preferable in vitro chemosensitivity assay that could be use to predict the response to chemotherapy and select the appropriate chemotherapy regimens for unresectable NSCLC patients, which could greatly improve therapeutic efficacy and reduce unnecessary adverse effects.

사업 초기단계에서 공동주택 토목공사비의 예측에 관한 연구 (A Study on the Prediction of Civil Construction Cost on Apartment Housing Projects at the Early Stage)

  • 하규수;이진규
    • 한국산학기술학회논문지
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    • 제13권9호
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    • pp.4284-4293
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    • 2012
  • 건설사업 수행의 초기단계에서 가장 중요한 과제는 적정 예정공사비를 산정하는 일이다. 따라서 본 연구에서는 공동주택 건설사업 초기단계에서 합리적이고 정확한 토목공사비의 예측을 위하여 170개의 공사비자료를 활용한 회귀분석을 실시하였고, 종속변수인 토목공사비를 지역위치에 따른 전국, 부지조건에 따른 사유지, 조합부지, 공공부지로 구분하여 다양한 분석을 함으로써 예측모델의 이용의 편리성과 정확성을 높였다. 회귀식을 이용한 공동주택 토목공사비의 예측 결과 오차율은 전국 적용 예측모델 15.59%, 사유지 적용 예측모델 17.53%, 조합부지 적용 예측모델 21.86%, 공공부지 적용 예측모델 13.08%로 나타났다.