Search Results - (( text classification using algorithm ) OR ( based constructive method algorithm ))
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1
Knowledge base processing method based on text classification algorithm
Published 2023“…The text classification algorithm's knowledge base processing method utilizes existing data from the knowledge base to guide the construction and training of the classification model. …”
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Aco-based feature selection algorithm for classification
Published 2022“…The modified graph clustering ant colony optimisation (MGCACO) algorithm is an effective FS method that was developed based on grouping the highly correlated features. …”
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Thesis -
3
Optimized feature construction methods for data summarizations of relational data
Published 2014“…In this thesis, novel feature construction methods are introduced and a question of whether or not the descriptive accuracy of the summarized data can benefit from the novel feature construction methods is investigated. …”
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4
Ant colony optimization based subset feature selection in speech processing: Constructing graphs with degree sequences
Published 2024journal::journal article -
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An evolutionary based features construction methods for data summarization approach
Published 2015“…In this work, we empirically compare the predictive accuracies of classification tasks based on the proposed feature construction methods and also the existing feature construction methods. …”
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Research Report -
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Non-fiducial based electrocardiogram biometrics with kernel methods
Published 2017“…The effectiveness of this algorithm is investigated by comparing with other AC based feature extraction algorithms involving AC/LDA (Linear Discriminant Analysis) and AC/PCA (Principal Component Analysis). …”
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Multi-label learning based on positive label correlations using predictive apriori
Published 2019“…Along with that, two algorithms have been constructed by capturing the positive correlations where the first algorithm (MLR-PC) captures the positive global correlations and the second algorithm (MLCBA) proposes an adaption of AC algorithm to handle MLC based on the positive local correlations. …”
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9
An ensemble method with cost function on churn prediction
Published 2019“…Therefore, this paper aims to achieve higher classification accuracy and at the same time, minimising ensemble classifiers by constructing a new ensemble method based on dimensionality reduction in soft set theory. …”
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10
Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection
Published 2020“…Four state-of-the-art algorithms include particle swarm optimization, flower pollination algorithm, butterfly optimization algorithm, and CBGWO are used to examine the effectiveness of proposed methods in feature selection. …”
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Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level
Published 2024thesis::doctoral thesis -
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AUTONOMOUS POWER LINE INSPECTION USING COMPUTER VISION
Published 2022“…DenseNet-201 model is proposed as the base network to perform insulator fault detection autonomously. …”
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Final Year Project Report / IMRAD -
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An improved multiple classifier combination scheme for pattern classification
Published 2015“…A compactness measure is introduced as a parameter in constructing an accurate and diverse classifier ensemble. …”
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Classification of leibniz algebras over finite fields
Published 2019“…The main idea of the annihilator extension is to transfer the “base change” action to an action of the automorphism group of the algebras of smaller dimension on cocycles constructed by the extension. …”
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16
A Framework For Classification Software Security Using Common Vulnerabilities And Exposures
Published 2018“…This inclusive of the investigation of vulnerability classification objectives,processes,classifiers and focus domains among prominent framework.Final step is to construct the framework by establishing the formal presentation of the vulnerability classification algo-rithm.The validation process was conducted empirically using statistical method to assess the accuracy and consistency by using the precision and recall rate of the algorithm on five data sets each with 500 samples.The findings show a significant result with precision's error rate or p value is between 0.01 and 0.02 with error rate for recall's error rate is between 0.02 and 0.04.Another validation was conducted to verify the correctness of the classification by using expert opinions,and the results showed that the ambiguity of several cases were subdue. …”
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17
Malicious URL Detection with Distributed Representation and Deep Learning
Published 2023Conference Paper -
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Speaker identification through feature fusion based deep learning / Rashid Jahangir
Published 2021“…In addition, DNN obtained better classification results compared with the other five machine learning algorithms that were recently utilised in speaker recognition. …”
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Application Of Slantlet Transform Based Support Vector Machine For Power Quality Detection And Classification
Published 2015“…Finally, sensitivity of the proposed algorithm under noisy condition is investigated in this paper.…”
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