Alternative Methods of Estimating the Likelihood Ratio in Classification of Multivariate Normal Observations

1979 ◽  
Vol 33 (4) ◽  
pp. 204 ◽  
Author(s):  
Chien-Pai Han
Keyword(s):  
Likelihood Ratio ◽  
Alternative Methods ◽  
Multivariate Normal

scholarly journals Classification of Thyroid Nodules with Stacked Denoising Sparse Autoencoder

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Zexin Li ◽  
Kaiji Yang ◽  
Lili Zhang ◽  
Chiju Wei ◽  
Peixuan Yang ◽  
...  
Keyword(s):  
Likelihood Ratio ◽  
Predictive Value ◽  
Thyroid Nodules ◽  
Area Under The Curve ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Discriminative Ability ◽  
Sparse Autoencoder ◽  
Immune Related Genes

Purpose. Several commercial tests have been used for the classification of indeterminate thyroid nodules in cytology. However, the geographic inconvenience and high cost confine their widespread use. This study aims to develop a classifier for conveniently clinical utility. Methods. Gene expression data of thyroid nodule tissues were collected from three public databases. Immune-related genes were used to construct the classifier with stacked denoising sparse autoencoder. Results. The classifier performed well in discriminating malignant and benign thyroid nodules, with an area under the curve of 0.785 [0.638–0.931], accuracy of 92.9% [92.7–93.0%], sensitivity of 98.6% [95.9–101.3%], specificity of 58.3% [30.4–86.2%], positive likelihood ratio of 2.367 [1.211–4.625], and negative likelihood ratio of 0.024 [0.003–0.177]. In the cancer prevalence range of 20–40% for indeterminate thyroid nodules in cytology, the range of negative predictive value of this classifier was 37–61%, and the range of positive predictive value was 98–99%. Conclusion. The classifier developed in this study has the superb discriminative ability for thyroid nodules. However, it needs validation in cytologically indeterminate thyroid nodules before clinical use.

Some methods of combining class information in multivariate normal discrimination for the classification of human chromosomes

1991 ◽  
Vol 10 (1) ◽  
pp. 141-149 ◽  
Author(s):  
S. P. J. Kirby ◽  
C. M. Theobald ◽  
J. Piper ◽  
A. D. Carothers
Keyword(s):  
Human Chromosomes ◽  
Multivariate Normal ◽  
Class Information

scholarly journals Learn from every mistake! Hierarchical information combination in astronomy

2016 ◽  
Vol 12 (S325) ◽  
pp. 39-45 ◽  
Author(s):  
Maria Süveges ◽  
Sotiria Fotopoulou ◽  
Jean Coupon ◽  
Stéphane Paltani ◽  
Laurent Eyer ◽  
...  
Keyword(s):  
Big Data ◽  
Probability Distributions ◽  
Variable Stars ◽  
Alternative Methods ◽  
Photometric Redshift ◽  
Promising Tool ◽  
Combination Methods ◽  
General Improvement ◽  
Output Probability

AbstractThroughout the processing and analysis of survey data, a ubiquitous issue nowadays is that we are spoilt for choice when we need to select a methodology for some of its steps. The alternative methods usually fail and excel in different data regions, and have various advantages and drawbacks, so a combination that unites the strengths of all while suppressing the weaknesses is desirable. We propose to use a two-level hierarchy of learners. Its first level consists of training and applying the possible base methods on the first part of a known set. At the second level, we feed the output probability distributions from all base methods to a second learner trained on the remaining known objects. Using classification of variable stars and photometric redshift estimation as examples, we show that the hierarchical combination is capable of achieving general improvement over averaging-type combination methods, correcting systematics present in all base methods, is easy to train and apply, and thus, it is a promising tool in the astronomical “Big Data” era.

Pre-treatment and elimination systems of toxic industrial waste and sludges. The case study of the department of Attika

1997 ◽  
Vol 36 (2-3) ◽  
pp. 91-100
Author(s):  
C. Malliaros ◽  
A. Guitonas
Keyword(s):  
Liquid Waste ◽  
Public Works ◽  
Toxic Waste ◽  
Alternative Methods ◽  
Toxic Substances ◽  
Pre Treatment ◽  
Evaluation Of Data ◽  
Methods Of Treatment

In the departments of Attika and Viotia there are about 1,100 industries. The total amount of produced waste from the above mentioned branches is 20 × 106 t/year, 600,000t of which contain toxic substances. By contract from October 1st, 1992 between the Ministry of the Environment, Regional Planning and Public Works and three collaborating offices (among them the office of C. Malliaros) has been assigned to the latter, the realisation of a study of the management of toxic waste (liquid) and sludges, in the Departments of Attika and Viotia. The study presented in this paper investigates the following: - collection and evaluation of data and estimation of the hydraulic and pollution loads - classification of industries according to sewage facilities - further possibilities for changes of improvements in the production process of the industrial branches for the reduction of pollution and representation of these industries on maps - proposals for the collection and transport of the liquid toxic waste and sludges - pre-treatment at the source and disposal of the liquid waste and sludges - presentation of administrative and legislative regulations - forming a policy for the management and monitoring of this waste - technical and financial evaluation and investigation of the alternative methods of treatment - suggestions for the development of the area concerning the activities and the expenses at various levels.

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