Search Results - (( data classification _ algorithm ) OR ( program validation learning algorithm ))
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1
Case Slicing Technique for Feature Selection
Published 2004“…One of the problems addressed by machine learning is data classification. Finding a good classification algorithm is an important component of many data mining projects. …”
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Thesis -
2
Predicting Student Performance in Object Oriented Programming Using Decision Tree : A Case at Kolej Poly-Tech Mara, Kuantan
Published 2013“…Using 10-fold cross validation for each algorithm, it was found that decision tree was the best algorithm with 83.6944% correctness. …”
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Conference or Workshop Item -
3
Face recognition using eigenfaces and smooth support vector machine
Published 2011“…Support Vector Machine (SVM) is a new algorithm of data mining technique, recently received increasing popularity in machine learning community. …”
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Undergraduates Project Papers -
4
Predicting students’ STEM academic performance in Malaysian secondary schools using educational data mining
Published 2023“…It proceeds through three phases of Need Analysis, Development of the Model and Evaluation of the Model. Four different data mining classification algorithms which are Random Forest, PART, J48 and Naive Bayes will be used on the dataset. …”
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5
Framework for pedestrian walking behaviour recognition to minimize road accident
Published 2021“…Fifthly, the performance of the proposed classification methods is validated and evaluated against multiple scenarios and features. …”
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6
Framework for pedestrian walking behaviour recognition to minimize road accident
Published 2021“…Fifthly, the performance of the proposed classification methods is validated and evaluated against multiple scenarios and features. …”
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7
Validation of deep convolutional neural network for age estimation in children using mandibular premolars on digital panoramic dental imaging / Norhasmira Mohammad
Published 2022“…The semi-automated dental staging system developed in this study is based on the Malay children’s population and uses a brain-inspired learning algorithm termed "deep learning". The methodology is comprised of four major steps: image preprocessing, which adheres to the inclusion criteria for panoramic dental radiographs, segmentation, and classification of mandibular premolars according to Demirjian's staging system using the Dynamic Programming-Active Contour (DP-AC) method and Deep Convolutional Neural Network (DCNN), respectively, and statistical analysis. …”
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8
Novice programmers’ emotion and competency assessments using machine learning on physiological data / Fatima Jannat
Published 2022“…There is also growing interest in modeling machine learning and deep learning algorithms that can learn from user’s data, understand and react to that individual’s affective state. …”
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9
Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…Methods for improving supervised and unsupervised classification of remotely sensed data were developed in this study. …”
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10
Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
Published 2020“…Nevertheless, there are some limitations in ID3 algorithm that can affect the performance in the classification of data. …”
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Article -
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Enhancing Classification Algorithms with Metaheuristic Technique
Published 2024“…However, the classification algorithm cannotclassify data optimally due to the challenges in dealing with variousdata sets. …”
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Article -
12
A multi-depot vehicle routing problem with stochastic road capacity and reduced two-stage stochastic integer linear programming models for rollout algorithm
Published 2021“…The results obtained from the resulting rollout policy with CPLEX execution during rollout are also presented to validate the reduced model and the matheuristic algorithm. …”
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Article -
13
Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd
Published 2022“…The study verified that the FID3-DBD algorithm could classify the continuous data, and the BFID3-DBD algorithm overcame the overfitting issue, reduced high variance, and increased test data classification accuracy.…”
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14
Dengue classification system using clonal selection algorithm / Karimah Mohd
Published 2012“…This project focused on three main objectives: to investigate dengue data and Clonal Selection Algorithm for classification of Dengue, to design and develops Clonal Selection Classification System (CSCS) and to evaluate Clonal Selection Classification System symptoms. …”
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15
System identification using Extended Kalman Filter
Published 2017“…In order to evaluate the performance of the EKF learning algorithm, the proposed algorithm validation were analyzed using model validation methods as a checker such as One Step Ahead (OSA) and correlation coefficient (R2). …”
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Student Project -
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Text Extraction Algorithm for Web Text Classification
Published 2010“…This study provides a text extraction algorithm for web text classification. The extraction algorithm consists of three phases namely web page extraction, rule formulation, and algorithm validation. …”
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Development of classification algorithms of human gait
Published 2022“…Thus, this study aims to develop a classification algorithm that can effectively classify subjects with relatively simplified input data. …”
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Final Year Project / Dissertation / Thesis -
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DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH
Published 2005“…The project's objective is identifying the available data mining algorithms in data classification and applying new data mining algorithm to perform classification tasks. …”
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Final Year Project -
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Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection
Published 2015“…The average classification accuracy of 99.47% on the test data achieved the acceptable average success rate. …”
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20
Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…The result has shown that the proposed integration system could be applied to increase the performance of the classification. However, further study is needed in the feature extraction and clustering algorithms part as the performance of the pattern classification is still depending on the data input.…”
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