Search Results - (( java implementation mining algorithm ) OR ( making process tree algorithm ))
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1
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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3
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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4
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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Final Year Project / Dissertation / Thesis -
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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7
Laptop price prediction using decision tree algorithm / Nurnazifah Abd Mokti
Published 2024“…The project involves data collection, data preparation, and the implementation of the decision tree algorithm for price prediction. The decision tree's effectiveness and accuracy in predicting laptop prices are evaluated through rigorous testing and validation. …”
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8
Amtree Protocol Enhancement by Multicast Tree Modification and Incorporation of Multiple Sources
Published 2008“…It is separated into three phases: 1) construction of multicast tree. 2) Handoff process. 3) Optimization Process. …”
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9
A new approach for convert multiply-connected trees in Bayesian networks
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Working Paper -
10
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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11
Optimizing tree planting areas through integer programming and improved genetic algorithm
Published 2012“…In conclusion, the hybrid algorithm based solution strategies improved efficiency with convincing results, therefore, this will assist planners for better decision making to optimize area to achieve more trees to be planted. …”
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12
Data Classification and Its Application in Credit Card Approval
Published 2004“…This project is involved with identification of the available algorithms used in data classification and the implementation of C4.5 decision tree induction algorithm in solving the data classifying task. …”
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Final Year Project -
13
Analysis and comparison of classification algorithms for credit approval in Islamic banks
Published 2025“…This study emphasizes the importance of selecting algorithms that address overfitting while maintaining robust predictive accuracy, contributing to improved decision-making in Islamic banking…”
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14
C4.5 Algorithm Application for Prediction of Self Candidate New Students in Higher Education
Published 2018“…To find out the prediction retirement prospective students, this paper uses C.45 algorithm. The method can change the a very large fact into a decision tree that represents the rule. …”
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Journal -
15
Prediction of Machine Failure by Using Machine Learning Algorithm
Published 2019“…Then, the data is cluster by using K Means to produce labeled input that will be trained by using Gradient Boosting Machine, a decision tree algorithm to make prediction. The columns consist of the variables that record the reading of machine sensor tags. …”
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Final Year Project -
16
Comparative study on data searching in linked list & B-tree and B+tree techniques
Published 2015“…Experimental results reveal that after the average times for each search algorithms on the databases have been recorded, the linked list requires lots of time during search process, with B+ tree producing significantly low times. …”
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17
Decision tree as knowledge management tool in image classification
Published 2008“…Expert System has been grown so fast as a science that study how to make computer capable of solving problems that typically can only be solved by expert.It has been realized that the biggest challenge of developing expert system is the process include expert’s knowledge into the system.This research tries to model expert’s knowledge management using case based reasoning method.The knowledge itself is not inputted directly by the expert, but rather the system will learn the knowledge from what the expert did to the previous cases.This research takes image classification as the problem to be solved.As the knowledge development technique, we build decision tree by using C4.5 algorithm.Variables used for building the decision tree are the image visual features.…”
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Conference or Workshop Item -
18
Evaluation of data mining classification and clustering techniques for diabetes / Tuba Pala and Ali Yilmaz Camurcu
Published 2014“…Multilayer Perceptron algorithm has been the best algorithm with the highest success percentage in both of the programs; Decision Trees has been the algorithm which has the lowest success percentage again in both of the programs. …”
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19
Correlation analysis and predictive performance based on KNN and decision tree with augmented reality for nuclear primary cooling process / Ahmad Azhari Mohamad Nor
Published 2024“…Practical algorithms incorporating k-nearest neighbour and decision tree models with quantifiable performance metrics are proposed to streamline and optimise the maintenance process. …”
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20
Prediction of Oil Palm Yield Using Machine Learning in the Perspective of Fluctuating Weather and Soil Moisture Conditions: Evaluation of a Generic Workflow
Published 2023“…Selected regression models were compared with Random Forest, Gradient Boosting, Decision Tree, and other non-tree algorithms to prove the R2 driven performance superiority of tree-based ensemble models. …”
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