Search Results - (( using complex ((data algorithm) OR (tree algorithm)) ) OR ( java application using algorithm ))
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Improvement on agglomerative hierarchical clustering algorithm based on tree data structure with bidirectional approach
Published 2024Conference Paper -
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An extended ID3 decision tree algorithm for spatial data
Published 2011“…Empirical result demonstrates that the proposed algorithm can be used to join two spatial objects in constructing spatial decision trees on small spatial dataset. …”
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Algorithm Development of Bidirectional Agglomerative Hierarchical Clustering Using AVL Tree with Visualization
Published 2024thesis::doctoral thesis -
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Improved Boosted Decision Tree Algorithms by Adaptive Apriori and Post-Pruning for Predicting Obstructive Sleep Apnea
Published 2018“…The post-pruning technique used is mainly the error-complexity pruning for the decision trees categorized under Classification and Regression Trees. …”
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Partial Binary Tree Network (Pbtn): A New Dynamic Element Matching (Dem) Approach To Current Steering Digital Analog Converter (Dac)
Published 2014“…In this research, a new DEM algorithm is proposed on Current-Steering DACs with Partial Binary Tree Network (PBTN) algorithm to overcome glitches transitions with low complexity. …”
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E2IDS: an enhanced intelligent intrusion detection system based on decision tree algorithm
Published 2022“…The model design is Decision Tree (DT) algorithm-based, with an approach to data balancing since the data set used is highly unbalanced and one more approach for feature selection. …”
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Speeding up index construction with GPU for DNA data sequences
Published 2011“…The advancement of technology in scientific community has produced terabytes of biological data.This datum includes DNA sequences.String matching algorithm which is traditionally used to match DNA sequences now takes much longer time to execute because of the large size of DNA data and also the small number of alphabets.To overcome this problem, the indexing methods such as suffix arrays or suffix trees have been introduced.In this study we used suffix arrays as indexing algorithm because it is more applicable, not complex and used less space compared to suffix trees.The parallel method is then introduced to speed up the index construction process. …”
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An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM)
Published 2024“…This study recommends a selection trade-off as the function of prediction efficiency and efficacy of the algorithm. Particularly, the proposed optimized Bagged Trees are the most effective algorithm for energy demand prediction applications, and the proposed optimized Medium Trees are the most efficient algorithm for real-time systems. …”
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Enhanced mechanism to handle missing data of Hadith classifier
Published 2011“…Decision tree algorithms have the ability to deal with missing values or wrong data. …”
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A Recent Research on Malware Detection Using Machine Learning Algorithm: Current Challenges and Future Works
Published 2023Conference Paper -
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Decision tree and rule-based classification for predicting online purchase behavior in Malaysia / Maslina Abdul Aziz, Nurul Ain Mustakim and Shuzlina Abdul Rahman
Published 2024“…The result indicated that the highest accuracy of 89.34% was achieved by the Random Tree algorithm, while the rule-based algorithm PART reached an accuracy of 87.56%. …”
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Optimized tree-classification algorithm for classification of protein sequences
Published 2016“…In this work, we have proposed an optimized tree-classification technique which uses cluster k nearest neighbor classification algorithm to classify protein sequences into superfamilies. …”
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Optimized tree-classification algorithm for classification of protein sequences
Published 2016“…In this work, we have proposed an optimized tree-classification technique which uses cluster k nearest neighbor classification algorithm to classify protein sequences into superfamilies. …”
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Classification of stock market index based on predictive fuzzy decision tree
Published 2005“…The experimental results show that the predictive FDT algorithm and fuzzy reasoning method provides the reasonable performance for comprehensibility (no of rules), complexity (no of nodes) and predictive accuracy of WFPRs for stock market time series data.…”
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An efficient indexing and retrieval of iris biometrics data using hybrid transform and firefly based K-means algorithm title
Published 2019“…For searches and retrieval, an efficient parallel technique has been presented by dividing the group of features into two b-trees based on index keys. Searches within a group can be done using a half-searching algorithm to improve the response time for data retrieval. …”
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Enhancement of medical image compression algorithm in noisy WLANS transmission
Published 2018“…For image reconstruction,decoding steps based the developed quantization architecture are examined.The EICA is particularly useful where the size of the transmitted data needs to be reduced to minimize the image transmission time.For data compression with suitable and effective performance,enhanced independent components analysis (EICA) is proposed as an algorithm for compression and decompression of medical data.A comparative analysis is performed based on existing data compression techniques:discrete cosine transform (DCT), set partitioning in hierarchical trees (SPIHT),and Joint Photographic Experts Group (JPEG 2000).Three main modules,namely,compression segment (CS),transceiver segment (TRS),and outcome segment (OTS) modules,are developed to realize a fully computerized simulation tool for medical data compression with suitable and effective performance.To compress medical data using algorithms,CS module involves four different approaches which are DCT, SPIHT,JPEG 2000 and EICA.TRS module is processed by low-cost WLANs with low-bandwidth transmission.Finally,OTS is used for data decompression and visualization result.In terms of compression module,results show the benefits of applying EICA in medical data compression and transmission.While for system design,the developed system displays favorable outcomes in compressing and transmitting medical data.In conclusion,all three modules (CS,TRS,and OTS) are integrated to yield a computerized prototype named as Medical Data Simulation System(Medata-SIM) computerized system that includes medical data compression and transceiver for visualization to aid medical practitioners in carrying out rapid diagnoses.…”
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Predicting Customer Behaviour on Buying Life Insurance using Machine Learning
Published 2026journal::journal article
