Method for Estimating Connection Power of Binary and Nominal Variables

Dronov, S. V.; Boyko, I. Yu.

doi:10.17223/20710410/30/11

Cited by 2 publications

(1 citation statement)

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“…Вышеизложенные рассуждения приводят к выводу о необходимости исследования взаимосвязи числового и бинарного признаков при решении проблемы отбора значимых признаков из данных с микрочипов. Распространенные на практике в настоящее время методы отбора признаков не вполне сосредоточены на выявлении связи рассматриваемого типа в силу ее существенной нелинейности, поэтому в следующих работах был введен ledge-коэффициент корреляции для оценивания силы такой связи, а также алгоритмы по его вычислению [30,31]. Далее нами предлагается критерий отбора значимых признаков из данных с микрочипов, который представляет собой алгоритм фильтрации, основанный на использовании ledge-коэффициента корреляции.…”

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Approach to The Selection of Significant Features in Solving Biomedical Problems of Binary Classification of Microarray Data

Boyko¹,

Anisimov²,

Smolyakova³

et al. 2020

Math.Biol.Bioinf.

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In modern biomedical research aimed at finding methods for early diagnosis of cancer, microarrays containing certain biological information about patients are used. Based on these data, patients are assigned to one of two classes, corresponding to the presence and absence of some diagnosis. When solving this problem, one of the steps that have a decisive influence on the quality of classification is the significant features selection. This paper proposes a criterion for the selection of significant features, based on the ledge-coefficient of correlation. The ledge-coefficient was previously used to estimate the degree of interrelation of numerical and binary features. For two sets of microarray data, comparative examples of their binary classification are presented using three feature selection algorithms, three dimensionality reduction methods, six classification models. The use of the ledge-criterion for feature selection made it possible to obtain a classification quality comparable to the results of using common methods of feature selection, such as t-test and U-test. For the data set of the peptide microarrays considered in the paper, the effectiveness of applying the projection method to latent structures had previously been identified. The use of this method in combination with the significant features’ selection using the ledge-criterion made it possible to obtain a higher classification quality measure.

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Approach to The Selection of Significant Features in Solving Biomedical Problems of Binary Classification of Microarray Data

Boyko¹,

Anisimov²,

Smolyakova³

et al. 2020

Math.Biol.Bioinf.

View full text Add to dashboard Cite

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A new statistical test for distinguishing 2-partitions of a finite set

Dronov¹

2022

MAS

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This paper considers a family of so-called 2-partitions of some finite set. Each of them divides the set under study into two disjoint parts. Under the assumption that two such partitions are chosen randomly, the exact probability distribution of the special cluster metric on this family is found. On this basis, a new statistical test for checking the significance of differences between 2-partitions is proposed. In addition, the distribution of the values of this metric is found for the case when both partitions are of the ledge type in ordering the set of objects in ascending order of values of some numerical indicator. This means that one of the parts of each partition, which in some sense is the main one, is a segment. The boundaries of such a segment are called normative. By comparing various estimates of the normative boundaries based on sample data, it is introduced the concept of indicative certainty of the numerical indicator. It can be regarded as the degree of confidence in this indicator as a basis for decision whether an object belongs to the main set of the ledge partition. Some application of the results to medical data processing is considered.

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Method for Estimating Connection Power of Binary and Nominal Variables

Cited by 2 publications

References 0 publications

Approach to The Selection of Significant Features in Solving Biomedical Problems of Binary Classification of Microarray Data

Approach to The Selection of Significant Features in Solving Biomedical Problems of Binary Classification of Microarray Data

A new statistical test for distinguishing 2-partitions of a finite set

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