Extensive Analysis on Generation and Consensus Mechanisms of Clustering Ensemble: A Survey

Rani, Yalamarthi Leela Sandhya; Sucharita, V.; Satyanarayana, K.

doi:10.11591/ijece.v8i4.pp2351-2357

Cited by 2 publications

(1 citation statement)

References 10 publications

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“…The inconsistencies detected or removed may have been initially caused by user entry errors, by changing in transmission or storage, or by different data dictionary definitions of similar entities in different stores. It differs from data validation in that validation almost invariably means data is rejected from the system at entry and is executed at the time of entry, rather than on batches of data [10]. The primary process of this is, it may involve removing typographical errors and correcting those values against a list of entities.…”

Section: Data Cleaningmentioning

confidence: 99%

Consumption of Food by College Students using Ml Algorithms

Sri*,

Susmitha,

Surya

et al. 2019

IJRTE

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We are well aware of the many problems that our current generations are facing. From all these new enhancements in the real world, it has been quite hard for them to keep up with everything evolving around them. Keeping all this in mind, they work day in and out to make sure that their knowledge of their surroundings up to date. However, we believe that they fail to take care of themselves in the process correctly. No matter how much a particular individual may withstand in terms of workload, stress, or other mental & emotional barriers, our physical body will always be the critical aspect to overcoming them. Most people believe that working out and maintaining physical fitness are the significant aspects to sustain an excellent physical form, but they simply overlook the most crucial element which is their eating habits [1]. Although our body may be physically fit, the nourishment of our body depends on the eating styles that we follow on a day to day basis. Food is what nourishes our body with most of the proteins & minerals that we require; without it, we wouldn't be able to accomplish much. On conducting worldwide research on people's lifestyles, we were able to conclude that over the past 33 years, the obesity rate among human beings has increased by a mere 27.5%. What seems to be the most thoughtful yet intriguing fact is that although many people are overweight as well as obese, they still believe that their eating habits are healthy [2]. Most people are living in the dilemma of the fact that they maintain a healthy lifestyle. We aim to study the views on a healthy lifestyle as per the norms of our current generation. We want to analyze their daily eating habits as well as their thoughts on their lifestyle. So the question that remains is “What exactly is a Healthy Eating Lifestyle?”[3]To know the accuracy of our data set we use the machine learning algorithms like Support Vector Machine (svm), Naïve-Bayes Classifier which are used for both classification and regression [4]

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Section: Data Cleaningmentioning

confidence: 99%

Consumption of Food by College Students using Ml Algorithms

Sri*,

Susmitha,

Surya

et al. 2019

IJRTE

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Ensemble learning based classifier to predict depression caused due to pandemic

Vaishali

Kumari

2021

J. Phys.: Conf. Ser.

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Pandemic caused due to Corona Virus Disease 2019 (COVID-19) affected each and every person life throughout the world. First wave of COVID-19 followed by second wave made situation more panic. Government declared Lockdown imposed strict prohibition on social gathering, unnecessary outing, travelling, and education. During home quarantine, people shared opinion, expressed views, feelings on social media. Home isolation and quarantine affected mental health of people which may lead to depression. Hence in this research article depression is predicted by implementing Neural Network based model. At first level this model implements text classification of COVID-19 based Tweets. Neural network model accuracy is 86.85%. In next level, using same tweet dataset as input, Ensemble learning based model is constructed. This model uses one of the boosting techniques known as Adaboost. Model is executed by varying Train-test-validation ratio. It is observed that accuracy of the model is improved. The model showed accuracy of 99.33 % successfully in every execution. Obtained results are compared with previous work in same area.

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Extensive Analysis on Generation and Consensus Mechanisms of Clustering Ensemble: A Survey

Cited by 2 publications

References 10 publications

Consumption of Food by College Students using Ml Algorithms

Consumption of Food by College Students using Ml Algorithms

Ensemble learning based classifier to predict depression caused due to pandemic

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