Search Results - (( text classification modeling algorithm ) OR ( using function based algorithm ))
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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…Expectation maximization (EM) is one of the representatives clustering algorithms which have broadly applied in solving classification problems by improving the density of data using the probability density function. …”
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New Learning Models for Generating Classification Rules Based on Rough Set Approach
Published 2000“…Classification rules were generated based on the best reduct. For the problem of missing data, a new approach was proposed based on data partitioning and function mode. …”
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Improved cuckoo search based neural network learning algorithms for data classification
Published 2014“…On the other hand, LM algorithms which are derivative based algorithms still face a risk of getting stuck in local minima. …”
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Jogging activity recognition using k-NN algorithm
Published 2022“…The k-NN algorithm is a simple and easy-to-implement supervised machine learning algorithm that can be used to solve both classification and regression problems. …”
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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification
Published 2019“…Second, propose an Optimized Time Sliding Window based Three Colour Marker. Finally, propose a new method of obtaining optimal parameters dropping functions for Random Early Detection (RED) algorithm. …”
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RLMD-PA: A Reinforcement Learning-Based Myocarditis Diagnosis Combined with a Population-Based Algorithm for Pretraining Weights
Published 2024journal::journal article -
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Agarwood oil quality classification using one versus all strategies in multiclass on SVM model / Aqib Fawwaz Mohd Amidon … [et al.]
Published 2021“…Support vector machine (SVM) has been chosen as a main model and for the specific function algorithm was multiclass function. Then, in the function, the one versus all (OVA) strategies has been used. …”
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…Based on the experiment results, the classification method using the TIP approach has successfully performed rules generation and classification tasks as required during a classification operation. …”
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…Therefore, this research has designed fuzzy learning algorithm that is able to classify fruits based on their shape and size features using Harumanis dataset. …”
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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Real-time intelligent recycle waste detection and classification using you only look once version 5 / Aiman Syafwan Amran
Published 2023“…Because of that, this project aims to detect and classify a typed of recycled waste such paper, plastic and metal. It uses YOLOv5 object detection and classification algorithm. …”
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Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm
Published 2018“…The problem of using range function in Heterogeneous Euclidean-Overlap Metric (HEOM) is addressed by replacing the range with interquartile range function called Interquartile Range-Heterogeneous Metric (IQR-HEOM). …”
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Diagnosis and treatment recommender system for myocardial infarction using decision tree and Support Vector Machines (SVM) / Wan Marzuqiamrin Wan Mansor
Published 2025“…If the ECG image is classified as indicative of myocardial infarction, the user inputs additional patient clinical data. The decision tree algorithm functions after this point. The prototype processes collected clinical data using these algorithms to confirm diagnoses while determining the level of patient severity. …”
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Backpropagation vs. radial basis function neural model : Rainfall intensity classification for flood prediction using meteorology data
Published 2016“…Among the various soft computing methods, Artificial Neural Network (ANN) is the most commonly used methodology. While numerous ANN algorithms were applied, the most commonly applied are the Backpropagation (BPN) and Radial Basis Function (RFN) models. …”
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Classification and visualization on eligibility rate of applicant’s LinkedIn account using Naïve Bayes / Nurul Atirah Ahmad
Published 2023“…The NB model achieved a commendable accuracy of 89.8%, indicating good performance in classifying potential job applicants. The system’s functionality based on the use case and usability tested by the Human Resources expert has been tested to evaluate its system requirements. …”
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Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection
Published 2020“…The proposed methods show superior results in several benchmark function tests. As for EMG feature selection, the proposed algorithms are evaluated using the EMG data acquired from the publicly access EMG database. …”
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Leveraging CQT-VMD and pre-trained AlexNet architecture for accurate pulmonary disease classification from lung sound signals
Published 2025“…Breathing sounds from the ICBHI and KAUHS databases are analyzed, where three key intrinsic mode functions (IMFs) are extracted using VMD and subsequently converted into CQT-based time-frequency representations. …”
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Improving Brain MR Image Classification for Tumor Segmentation using Phase Congruency
Published 2018“…MRI which stands for Magnetic Resonance Imaging is commonly used to capture images of internal body organs, functionality and structure. …”
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