Nearest Cluster Classifier

Parvïn, Hamïd; Mohamadi, Moslem; Parvin, Sajad; Rezaei, Zahra; Minaei, Behrouz

doi:10.1007/978-3-642-28942-2_24

Cited by 9 publications

(4 citation statements)

References 9 publications

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“…Overall, this study shows increasing of the chance of emotional divorce by family chosen spouses. This nding is the same as the results of a study that worked on the socio-demographic factors affecting divorce, according to which factors related to parents and family structure can be predictors of marital divorce (25). Therefore, it seems family chosen spouse can be a sign of the type of family structure and lack of decision-making independence, where the combination of these factors will increase marital con icts and subsequently the chances of emotional divorce.…”

Section: Discussionsupporting

confidence: 74%

The assessment of the associated factors of Emotional divorce among Iranian couples during the Covid19 Pandemic: A descriptive study

Sadeghzadeh

Ghodssi-ghassemabad

Hamdieh

et al. 2023

Preprint

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Background: Emotional divorce can be defined as an important factor in the boredom of the couple, the cooling of the relationship between them, the feeling of sadness and despair, and the lack of dependence of the couple on each other, which has irreparable consequences for the family. Therefore, the present study was designed to assess the affecting associated factors of emotional divorce among Iranian couples during the Covid19 pandemic. Methods: A descriptive-analytical study was performed on 900 men and women from 22 districts of Tehran who were selected by the available sampling methods from March to October 2021. Data collection tools are Guttmann demographic and Emotional Divorce Questionnaires. The Questionnaires were completed by the participants of the study. R 4.0.2 software was used to analyze the data, in addition, an independent t-test and chi-square were used to compare the subjects in terms of the emotional divorce. Also, the multiple logistic regression method was used to determine the independent factors affecting emotional divorce. Results: The results showed that the associated factors of emotional divorce include age, marriage rank, duration of the marriage, choosing the spouse by parents, the education level of the couple, the job of the couple, infection of Covid19, and having disputes before Covid19 infection outbreak. Conclusion: Emotional divorce is considered as a social harm which could be the prelude of legal divorce. Therefore, the study of affecting factors on it in any society can pave the way for culture-based interventions to reduce such social harms.

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Section: Discussionsupporting

confidence: 74%

The assessment of the associated factors of Emotional divorce among Iranian couples during the Covid19 Pandemic: A descriptive study

Sadeghzadeh

Ghodssi-ghassemabad

Hamdieh

et al. 2023

Preprint

View full text Add to dashboard Cite

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“…Salah satu teknik dalam data mining adalah klasifikasi, klasifikasi adalah tugas untuk memprediksi label kategori yang tidak diketahui sebelumnya untuk membedakan antara satu objek dengan objek lainnya berdasarkan atribut atau fitur [12]. Teknik klasifikasi yang paling populer adalah K-Nearest Neighbor (KNN) karena sangat sederhana dan mudah [13]. Namun ada juga algoritma klasifikasi K-Nearest Neighbor (MKNN) yang merupakan algoritma turunan dari KNN.…”

Section: Pendahuluanunclassified

Klasifikasi Tweet di Twitter dengan Menggunakan Metode K-Nearest Neighbor

Rahman

2022

jsisfotek

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Twitter is a social media and also a microblog that allows users to send and read short messages of no more than 280 characters as tweets. Tweet users are currently not limited in terms of age, information, and communication. The lack of information on tweets on Twitter results in a lot of information that is difficult to know the facts or intentions of the tweet. This can have negative impacts such as fraud, leading public opinion to negative. One of the topics that has been discussed in Indonesian society since March 2020. Coranavirus Disease 2019 (COVID-19) is a disease of the new type of coronavirus virus (SARS-CoV-2) that has taken the world by storm and the WHO has declared it a pandemic. As of March 10, 2022, 5.85 million Covid cases have been confirmed out of a total of 453 million cases in the world. This Covid-19 case can be a place for certain parties to disseminate information to the wider community. Tweet data obtained from social networks based on queries in Indonesian, this study aims to determine the pros or cons of the public or society against Covid-19. To find out that a tweet is counter can be done by looking at the existing tweets one by one, but this takes a long time and effort because of the large number of tweets. In this study using the K-Nearest Neighbor (KNN) method using as many as 1200 tweet data. Based on the research that has been done, it can be said that public sentiment in 2020 regarding COVID-19 tends to be negative, followed by positive and neutral opinions. But in 2021, as time goes by, public opinion tends to follow neutral.

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“…On a very high level, this is similar to cluster-based NNC where class specific training data (data with same labels) is summarized as (multiple) cluster centers and used as a reduced training set on which NNC is applied -this is also known as prototype-based classification (CC), with the simplest form where there is a single cluster/prototype per class (CC1). A variety of methods exists in literature that adopt this simple idea of data reduction [9,11,24,25,27,35]. These algorithms are designed with the goal of reducing the high computational & storage requirements of NNC.…”

Section: Related Workmentioning

confidence: 99%

Fruit-fly Inspired Neighborhood Encoding for Classification

Sinha

Ram

2021

Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery &Amp; Data Mining

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Inspired by the fruit-fly olfactory circuit, the Fly Bloom Filter [4] is able to efficiently summarize the data with a single pass and has been used for novelty detection. We propose a new classifier that effectively encodes the different local neighborhoods for each class with a per-class Fly Bloom Filter. The inference on test data requires an efficient FlyHash [6] operation followed by a high-dimensional, but very sparse, dot product with the per-class Bloom Filters. On the theoretical side, we establish conditions under which the predictions of our proposed classifier agrees with the predictions of the nearest neighbor classifier. We extensively evaluate our proposed scheme with 71 data sets of varied data dimensionality to demonstrate that the predictive performance of our proposed neuroscience inspired classifier is competitive to the nearest-neighbor classifiers and other single-pass classifiers. CCS CONCEPTS• Computing methodologies → Bio-inspired approaches; Supervised learning by classification; Online learning settings.

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Nearest Cluster Classifier

Cited by 9 publications

References 9 publications

The assessment of the associated factors of Emotional divorce among Iranian couples during the Covid19 Pandemic: A descriptive study

The assessment of the associated factors of Emotional divorce among Iranian couples during the Covid19 Pandemic: A descriptive study

Klasifikasi Tweet di Twitter dengan Menggunakan Metode K-Nearest Neighbor

Fruit-fly Inspired Neighborhood Encoding for Classification

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