نتایج جستجو برای: probability plot correlation coefficient

تعداد نتایج: 748057  

Journal: :The Open Medical Informatics Journal 2008

Journal: :Journal of the Italian Statistical Society 1995

Journal: :Turkiye Klinikleri Journal of Biostatistics 2020

Journal: :Applied Mechanics and Materials 2013

2012
Antonio Fernández Orquín Yoan Gutiérrez-Vázquez Héctor Dávila Alexander Chavez Andy González Rainel Estrada Yenier Castañeda Sonia Vázquez Andrés Montoyo Rafael Muñoz

This paper describes the specifications and results of UMCC_DLSI system, which participated in the first Semantic Textual Similarity task (STS) of SemEval-2012. Our supervised system uses different kinds of semantic and lexical features to train classifiers and it uses a voting process to select the correct option. Related to the different features we can highlight the resource ISR-WN used to e...

2017
Shyamali Pal

The presence of Macro prolactin is a significant cause of elevated prolactin resulting in misdiagnosis in all automated systems. Poly ethylene glycol (PEG) pretreatment is the preventive process but such process includes the probability of loss of a fraction of bioactive prolactin. Surprisingly, PEG treated EQAS & IQAS samples in Cobas e 411 are found out to be correlating with direct results o...

1995
Leonid Golinskii Paul Nevai Walter Van Assche WALTER VAN ASSCHE

Orthogonal polynomials on the unit circle are completely determined by their reflection coefficients through the Szegő recurrences. We assume that the reflection coefficients converge to some complex number a with 0 < |a| < 1. The polynomials then live essentially on the arc { e : α ≤ θ ≤ 2π−α } where cos α 2 def = √ 1− |a|2 with α ∈ (0, π). We analyze the orthogonal polynomials by comparing th...

Journal: :CoRR 2016
Alexandre Fioravante de Siqueira Flávio Camargo Cabrera Aylton Pagamisse Aldo Eloizo Job

This study consolidates Multi-Level Starlet Segmentation (MLSS) and Multi-Level Starlet Optimal Segmentation (MLSOS), techniques for photomicrograph segmentation that use starlet wavelet detail levels to separate areas of interest in an input image. Several segmentation levels can be obtained using Multi-Level Starlet Segmentation; after that, Matthews correlation coefficient (MCC) is used to c...

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