Search Results - (( _ relations between algorithm ) OR ( data classification based algorithm ))*
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…In cluster labelling process, a cluster labelling algorithm based on calculation of minimum-distance (MD) between cluster mean and class mean was developed to label the clusters. …”
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Utilisation of Exponential-Based Resource Allocation and Competition in Artificial Immune Recognition System
Published 2011“…Artificial Immune Recognition System is one of the several immune inspired algorithms that can be used to perform classification, a data mining task. …”
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Analysis of Sentiment Based on Opinions from the 2019 Presidential Election
Published 2024“…These results indicate that the Naive Bayes Classifier is effective in distinguishing between positive and negative sentiments in tweets related to the presidential election.…”
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Deep learning-based colorectal cancer classification using augmented and normalised gut microbiome data / Mwenge Mulenga
Published 2022“…While the complex relations that exist between the microbiome and host phenotypes make machine learning algorithms suitable for analysing the microbiome data, deep learning methods are becoming more popular due to their outstanding performance in related fields. …”
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A Comparison Of The Different Algorithms For Essential Tremor And Parkinson’s Disease Tremor Differentiation Based On Hand Tremor
Published 2018“…Four different types of tremor classification algorithms, namely the Tremor Stability Index (TSI), Mean Harmonic Peak Power (MHPP), Relative Energy (RE) and Empirical Mode Decomposition – Singular Value Decomposition (EMD-SVD) analysis had been tested with 153 postural tremor recordings and 154 rest tremor recordings collected from ET and PD patients. …”
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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An automatic grading model for semantic complexity of english texts using bidirectional attention-based autoencoder
Published 2024“…The experimental results show that the overall accuracy of BSETG algorithm is maintained between 70% and 90%, the response speed of BSETG algorithm is relatively fast, and the success rate of BSETG algorithm is relatively stable to a large extent.…”
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PREDICTION OF HFMD DISEASE OUTBREAK FROM TWITTER
Published 2019“…On the other hand, Naive Bayes and SVM algorithm is using in classification of the tweets related with HFMD disease. …”
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Final Year Project Report / IMRAD -
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Evaluation and optimization of frequent, closed and maximal association rule based classification
Published 2014“…Real world applications of association rule mining have well-known problems of discovering a large number of rules, many of which are not interesting or useful for the application at hand.The algorithms for closed and maximal item sets mining significantly reduce the volume of rules discovered and complexity associated with the task, but the implications of their use and important differences with respect to the generalization power, precision and recall when used in the classification problem have not been examined.In this paper, we present a systematic evaluation of the association rules discovered from frequent, closed and maximal item set mining algorithms, combining common data mining and statistical interestingness measures, and outline an appropriate sequence of usage.The experiments are performed using a number of real-world datasets that represent diverse characteristics of data/items, and detailed evaluation of rule sets is provided as a whole and w.r.t individual classes. …”
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Classification with degree of importance of attributes for stock market data mining
Published 2004“…The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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Finger Motion In Classifying Offline Handwriting Patterns
Published 2017“…The preprocessed data is classified using the J48 tree algorithm. …”
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Monograph -
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Comparison between fuzzy and non-fuzzy classification methods in the prediction of residential household water leakage / Nor Aishah Md Noh, Dr. Khairul Anwar Rasmani and Nur Rasyid...
Published 2013“…The aim of this research is to predict residential households water leakage using models created based on training data with fuzzy rule-based and non-fuzzy rule-based algorithms available in WEKA Machine Learning Software (Witten and Frank, 2005). …”
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A Rough Set-Based Approach for Identifying and Replacing Missing Concepts in Incomplete Sentences in Computer Domain Texts
Published 2026thesis::master thesis -
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Developing framework for natphoric computer-aided web-based kansei engineering / Mohammad Bakri Che Haron
Published 2013“…The Natphoric algorithm learns the process done by training with sets of training data from previous KE research works. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…Hybridizing the Deep Neural Network (DNN) with the K-Means Clustering algorithm will increase the accuracy and reduce the data complexity of the Lorenz dataset. …”
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Correlation-based subset evaluation of feature selection for dynamic Malaysian sign language
Published 2016“…The sample of 3D data coordinates of X, Y, and Z axis is a value relative to the torso and head. …”
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Classification Of Gender Using Global Level Features In Fingerprint For Malaysian Population
Published 2016“…A new approach of algorithm based on the Mark Acree’s theory, focusing on fingerprint global extracted features is proposed and implemented for enhancing gender classification method. …”
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Evaluation of land use land cover changes impacts on water quality at Nerus River using geospatial techniques / Noor Azzatul Najwa Azman
Published 2021“…Other than that, Microsoft Excel also been used to calculate the WQI for each station using WQI algorithm. Overall, the result of this study carried out the relationship between Land use land cover (LULC) change and water quality index (WQI).…”
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