Search Results - (( developing intervention model algorithm ) OR ( java implementation mining algorithm ))
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Direct approach for mining association rules from structured XML data
Published 2012“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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Thesis -
2
Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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Scalable approach for mining association rules from structured XML data
Published 2009“…Many techniques have been proposed to tackle the problem of mining XML data we study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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Mining association rules from structured XML data
Published 2009“…Many techniques have been proposed to tackle the problem of mining XML data. We study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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5
A web-based implementation of k-means algorithms
Published 2022“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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6
Image clustering comparison of two color segmentation techniques
Published 2010“…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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8
i-Saturate: The New Discovery of Stopping Criterion in Genetic Algorithm
Published 2020“…It was concluded that the i-Saturate model has demonstrated better searching ability than the comparative model and it intelligently stops searching without human intervention.…”
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Determining malaria risk factors in Abuja, Nigeria using various statistical approaches
Published 2018“…The optimal model based on the parsimony principles was obtained from the hill climbing algorithm with score metrics. …”
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11
VISUALIZATION OF GENETIC ALGORITHM BASED ON 2-D GRAPH TO ACCELERATE THE SEARCHING WITH HUMAN INTERVENTIONS.
Published 2012“…It is noted that active user intervention increases the acceleration of Genetic Algorithm towards an optimal solution. …”
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12
Predictive Modelling of Stroke Occurrence among Patients using Machine Learning
Published 2023“…Advanced machine learning algorithms, including logistic regression, decision trees, random forests, and support vector machines, were utilized to analyses the dataset and develop a predictive model. …”
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Fine-scale predictive modeling of Aedes mosquito abundance and dengue risk indicators using machine learning algorithms with microclimatic variables
Published 2025“…This study developed fine-scale predictive models using machine learning algorithms; Artificial Neural Networks (ANN), Random Forest (RF), and Support Vector Machines (SVM) to estimate mosquito abundance and dengue risk at the species level based on daily microclimatic data (temperature, relative humidity, and rainfall) collected over 26 weeks in Kuala Selangor, Malaysia. …”
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Prediction of UiTM student academic performance using Naive Bayes algorithm / Muhammad Irfan Zahin Jailani
Published 2024“…With the help of customized interventions and early identification of at-risk pupils, the proposed approach seeks to increase graduation rates and overall achievement.The main objectives of this study include studying the Naive Bayes algorithm in student academic performance prediction, designing and developing a student academic performance prediction model utilizing Naive Bayes, and evaluating the accuracy of the prediction prototype using the developed model. …”
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Reliability fuzzy clustering algorithm for wellness of elderly people
Published 2019“…Fuzzy clustering is one of the unsupervised machine learning techniques based knowledge of data analysis that automated or semi-automated analytical model building. By gleaning insights from the data, the fuzzy clustering can learn from data, identify patterns and make decisions with minimal human intervention. …”
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Facility location models development to maximize total service area
Published 2009“…This paper present and discuss the new developed model to maximize total service area of a fixed number of facilities. …”
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Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr...
Published 2024“…This paper�s novelty includes introducing a new method for selecting inputs and developing a new model for predicting water levels. …”
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Comparison of hidden Markov Model and Naïve Bayes algorithms among events in smart home environment
Published 2014“…In this paper, we propose Hidden Markov Model (HMM) and Naïve Bayes (NB) to test the accuracy and response time of the home data and to compare between the two algorithms. …”
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Meta-requirement mapping model
Published 2020“…Looking forward, an algorithm will be developed for realizing the associations that was define in the propose model.…”
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