• Title/Summary/Keyword: Fisher's method

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Combining Independent Permutation p-Values Associated with Multi-Sample Location Test Data

  • Um, Yonghwan
    • Journal of the Korea Society of Computer and Information
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    • v.25 no.7
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    • pp.175-182
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    • 2020
  • Fisher's classical method for combining independent p-values from continuous distributions is widely used but it is known to be inadequate for combining p-values from discrete probability distributions. Instead, the discrete analog of Fisher's classical method is used as an alternative for combining p-values from discrete distributions. In this paper, firstly we obtain p-values from discrete probability distributions associated with multi-sample location test data (Fisher-Pitman test and Kruskall-Wallis test data) by permutation method, and secondly combine the permutaion p-values by the discrete analog of Fisher's classical method. And we finally compare the combined p-values from both the discrete analog of Fisher's classical method and Fisher's classical method.

Combining Independent Permutation p Values Associated with Mann-Whitney Test Data

  • Um, Yonghwan
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.7
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    • pp.99-104
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    • 2018
  • In this paper, we compare Fisher's continuous method with an exact discrete analog of Fisher's continuous method from permutation tests for combining p values. The discrete analog of Fisher's continuous method is known to be adequate for combining independent p values from discrete probability distributions. Also permutation tests are widely used as alternatives to conventional parametric tests since these tests are distribution-free, and yield discrete probability distributions and exact p values. In this paper, we obtain permutation p values from discrete probability distributions using Mann-Whitney test data sets (real data and hypothetical data) and combine p values by the exact discrete analog of Fisher's continuous method.

SOLVING THE GENERALIZED FISHER'S EQUATION BY DIFFERENTIAL TRANSFORM METHOD

  • Matinfar, M.;Bahar, S.R.;Ghasemi, M.
    • Journal of applied mathematics & informatics
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    • v.30 no.3_4
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    • pp.555-560
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    • 2012
  • In this paper, differential transform method (DTM) is considered to obtain solution to the generalized Fisher's equation. This method is easy to apply and because of high level of accuracy can be used to solve other linear and nonlinear problems. Furthermore, is capable of reducing the size of computational work. In the present work, the generalization of the two-dimensional transform method that is based on generalized Taylor's formula is applied to solve the generalized Fisher equation and numerical example demonstrates the accuracy of the present method.

Emotion Recognition Method Using FLD and Staged Classification Based on Profile Data (프로파일기반의 FLD와 단계적 분류를 이용한 감성 인식 기법)

  • Kim, Jae-Hyup;Oh, Na-Rae;Jun, Gab-Song;Moon, Young-Shik
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.48 no.6
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    • pp.35-46
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    • 2011
  • In this paper, we proposed the method of emotion recognition using staged classification model and Fisher's linear discriminant. By organizing the staged classification model, the proposed method improves the classification rate on the Fisher's feature space with high complexity. The staged classification model is achieved by the successive combining of binary classification model which has simple structure and high performance. On each stage, it forms Fisher's linear discriminant according to the two groups which contain each emotion class, and generates the binary classification model by using Adaboost method on the Fisher's space. Whole learning process is repeatedly performed until all the separations of emotion classes are finished. In experimental results, the proposed method provides about 72% classification rate on 8 classes of emotion and about 93% classification rate on specific 3 classes of emotion.

Modified Fisher method for unilateral cleft lip-report of cases

  • Kim, Hui Young;Park, Joonhyoung;Chang, Ming-Chih;Song, In Seok;Seo, Byoung Moo
    • Maxillofacial Plastic and Reconstructive Surgery
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    • v.39
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    • pp.12.1-12.5
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    • 2017
  • Background: Rehabilitation of normal function and form is essential in cleft lip repair. In 2005, Dr. David M. Fisher introduced an innovative method, named "an anatomical subunit approximation technique" in unilateral cleft lip repair. According to this method, circumferential incision along the columella on cleft side of the medial flap is continued to the planned top of the Cupid's bow in straight manner, which runs parallel to the unaffected philtral ridge. Usually, small inlet incision is needed to lengthen the medial flap. On lateral flap, small triangle just above the cutaneous roll is used to prevent unesthetic shortening of upper lip. This allows better continuity of the Cupid's bow and ideal distribution of tension. Case presentation: As a modification to original method, orbicularis oris muscle overlapping suture is applied to make the elevated philtral ridge. Concomitant primary rhinoplasty also results in good esthetic outcome with symmetric nostrils and correction of alar web. As satisfactory results were obtained in three incomplete and one complete unilateral cleft lip patients, indicating Fisher's method can be useful in cleft lip surgery with functional and esthetic outcome. Conclusions: Clinically applied Fisher's method in unilateral cleft lip patients proved the effectiveness in improving the esthetic results with good symmetry. This method also applied with primary rhinoplasty.

A Text Mining-based Intrusion Log Recommendation in Digital Forensics (디지털 포렌식에서 텍스트 마이닝 기반 침입 흔적 로그 추천)

  • Ko, Sujeong
    • KIPS Transactions on Computer and Communication Systems
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    • v.2 no.6
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    • pp.279-290
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    • 2013
  • In digital forensics log files have been stored as a form of large data for the purpose of tracing users' past behaviors. It is difficult for investigators to manually analysis the large log data without clues. In this paper, we propose a text mining technique for extracting intrusion logs from a large log set to recommend reliable evidences to investigators. In the training stage, the proposed method extracts intrusion association words from a training log set by using Apriori algorithm after preprocessing and the probability of intrusion for association words are computed by combining support and confidence. Robinson's method of computing confidences for filtering spam mails is applied to extracting intrusion logs in the proposed method. As the results, the association word knowledge base is constructed by including the weights of the probability of intrusion for association words to improve the accuracy. In the test stage, the probability of intrusion logs and the probability of normal logs in a test log set are computed by Fisher's inverse chi-square classification algorithm based on the association word knowledge base respectively and intrusion logs are extracted from combining the results. Then, the intrusion logs are recommended to investigators. The proposed method uses a training method of clearly analyzing the meaning of data from an unstructured large log data. As the results, it complements the problem of reduction in accuracy caused by data ambiguity. In addition, the proposed method recommends intrusion logs by using Fisher's inverse chi-square classification algorithm. So, it reduces the rate of false positive(FP) and decreases in laborious effort to extract evidences manually.

Fractal Image Compression Using QR Algorithm (QR 알고리즘을 이용한 프렉탈 영상압축)

  • Han, Kun-Hee;Kim, Tae-Ho;Jun, Byoung-Min
    • Journal of the Korean Society of Industry Convergence
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    • v.3 no.4
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    • pp.369-378
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    • 2000
  • Conventional fractal image compression methods have many problems in searching time for matching domain block. Proposed method is an improved method of Fisher's Quadtree Decomposition in terms of time, compression ratio, and PSNR. This method determines range block in advance using QR algorithm. First, input image is partitioned to $4{\times}4$ range block and then recomposition is performed from bottom level to specified level. As a result, this proposed method achieves high encoding and decoding speed, high compression ratio, and high PSNR than Fisher's Quadtree Decomposition method.

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A Comparative Study on Tests of Correlation (상관계수에 대한 검정법 비교)

  • Cho, Hyun-Joo;Song, Myung-Unn;Jeong, Dong-Myung;Song, Jae-Kee
    • Journal of the Korean Data and Information Science Society
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    • v.7 no.2
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    • pp.235-245
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    • 1996
  • In this paper, we studied about several methods of testing hypothesis of correlation, specially Approximate method, Empirical method and Bootstrap method. The Approximate method is based on the Fisher's Z-transformation and the Empirical and Bootstrap methods approximate the distribution of the sample correlation coefficient by Monte Carlo simulation and Bootstrap technique, respectively. In order to compare how good these tests are, we computed powers under various alternatives. Consequently, we see that the Approximate test performs very well even if in small sample and all tests have almost the same power in large sample.

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Soft Sensor Design Using Image Analysis and its Industrial Applications Part 2. Automatic Quality Classification of Engineered Stone Countertops (화상분석을 이용한 소프트 센서의 설계와 산업응용사례 2. 인조대리석의 품질 자동 분류)

  • Ryu, Jun-Hyung;Liu, J. Jay
    • Korean Chemical Engineering Research
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    • v.48 no.4
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    • pp.483-489
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    • 2010
  • An image analysis-based soft sensor is designed and applied to automatic quality classification of product appearance with color-textural characteristics. In this work, multiresolutional multivariate image analysis (MR-MIA) is used in order to analyze product images with color as well as texture. Fisher's discriminant analysis (FDA) is also used as a supervised learning method for automatic classification. The use of FDA, one of latent variable methods, enables us not only to classify products appearance into distinct classes, but also to numerically and consistently estimate product appearance with continuous variations and to analyze characteristics of appearance. This approach is successfully applied to automatic quality classification of intermediate and final products in industrial manufacturing of engineered stone countertops.

Performance Improvement of LVQ Network for Pattern Classification (패턴 분류를 위한 LVQ 네트워크의 성능 개선)

  • 정경권;이정훈;김주웅;손동설;엄기환
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2003.05a
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    • pp.245-248
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    • 2003
  • In this paper, we propose a learning method of the performance improvement of the LVQ network using the radios of the hypersphere with the n-dimensional input vectors. The proposed method determines the reference vectors using the radius of the hypersphere include n+1 set of input vectors in the same class. In order to verify the effectiveness of the proposed method, we performed experiments on the Fisher's IRIS data. The experimental results showed that the proposed method improves considerably on the performance of the conventional LVQ network.

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