Multi agent systems in distributed datawarehousing

Latchoumi, T. P.; Sunitha, R

doi:10.1109/iccct.2010.5640491

Cited by 6 publications

(3 citation statements)

References 13 publications

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“…Employee churn can be determined as leak or departure of creative central from the company [2]. The analysis is said as voluntary turnover.…”

Section: Literature Surveymentioning

confidence: 99%

Efficient Data Mining Model for Employees Churn Prediction and Safety Measure

Viswanadapalli¹

2021

pae

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Employee Churn which is otherwise called representative turnover is an exorbitant issue for organizations. The genuine expense for supplanting a worker can frequently be very enormous. In this work, we aimed to understand why and when employees are most likely to leave a company i.e the probability of an active employee leaving the organization and the key factors of an employee leaving the organization. For this purpose, we created such standard dataset where we include those attributes that are helpful for our analysis to predict the factors that are responsible for an employee to leave a company. The attributes we used in the dataset are satisfaction level, last evaluation, a number of projects, monthly average hours, amount of time spend in the company, employees left the company, promotions in last 5years, departments, salary. Further, under these attributes, we include 603 data samples. It is also useful to the company to retain the employees' safety and secure without losing them in the organization for a long time. We applied various Machine Learning models such as, Logistic Regression Classifier, Random Forest Classifier, SVM to check that our dataset is resulting with accurate values or not and which model is predicting the best. Thus, after applying all the models to the dataset, the Random Forest Classifier is giving more accuracy that is about 97.2% when compared to all the other classification models. This Random Forest Classifier correctly depicts the factors responsible for an employee leaving the company.

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“…Employee churn can be determined as leak or departure of creative central from the company [2]. The analysis is said as voluntary turnover.…”

Section: Literature Surveymentioning

confidence: 99%

Efficient Data Mining Model for Employees Churn Prediction and Safety Measure

Viswanadapalli¹

2021

pae

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“…The first laryngoscopy medical procedure will be performed to speculate on cancer of the throat which provides a closer view of the throat. If any abnormalities are found, then biopsy such as conventional Fine Needle Aspiration (FNA) biopsy or endoscopic biopsy is done as suggested by specialists [4]. If cancerous cells are detected, extra imaging testing of the head, neck, and chest will be done at that stage to hypothesize the disease process that ranges from 0 to 4.…”

Section: Introductionmentioning

confidence: 99%

Identification of Throat Cancer by Machine Learning : A Surey

Akshara¹

2021

TURCOMAT

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Medical applications in Machine Learning (ML) algorithms is well-being state on analyzing the different attributes that have a high impact on getting illness. Cancer is one amoungof the human disease where researchers are still struggling for the complete cureness and it is also unpredictable. Cancer is a heterogeneous disease and its treatment varies from one type to another and can inculcate different phases. Throat cancer is a tumor that spreads throughout the voice box (larynx), tonsils, or throat (pharynx). In the initial stage, it is actively recommended to diagnose throat cancer and get proper medication. Deep Learning (DL) image processing techniques and ML techniques are used to effectively predict the throat cancer specifically for the supervised learning classification algorithms. This paper reviewed theML and DLbased researchactivities undertaken to classify cancer of the throat cancer.

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“…The proxy serves as the place holder for a set of security enforcement. [19,21] presented multiagent systems models that operate in distributed systems and warehousing environments, with emphasis on the multiagency, while attention was not paid to security issues. The approach described in [23] explains a method of representing security and audit rules for DW at the logical level by using common warehouse meta-model.…”

Section: Introductionmentioning

confidence: 99%

A Secured Agent-Based Framework for Data Warehouse Management

Blamah¹

2013

IOSR-JCE

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Multi agent systems in distributed datawarehousing

Cited by 6 publications

References 13 publications

Efficient Data Mining Model for Employees Churn Prediction and Safety Measure

Efficient Data Mining Model for Employees Churn Prediction and Safety Measure

Identification of Throat Cancer by Machine Learning : A Surey

A Secured Agent-Based Framework for Data Warehouse Management

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