Search Results - (( model evaluation _ algorithm ) OR ( text classification modeling algorithm ))
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1
An adaptive ant colony optimization algorithm for rule-based classification
Published 2020“…Differing from other complex and difficult classification models, rules-based classification algorithms produce models which are understandable for users. …”
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Thesis -
2
Intent-IQ: customer’s reviews intent recognition using random forest algorithm
Published 2025“…Data annotation using semi-supervised learning which is self-training technique need to be accomplished as the dataset is unlabeled. Two machine learning model is chosen to build the classification models which are Random Forest (RF) algorithm and Multinomial Naïve Bayes (MNB) algorithm. …”
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3
Building classification models from imbalanced fraud detection data / Terence Yong Koon Beh, Swee Chuan Tan and Hwee Theng Yeo
Published 2014“…This paper reports our experience in applying data balancing techniques to develop a classifier for an imbalanced real-world fraud detection data set. We evaluated the models generated from seven classification algorithms with two simple data balancing techniques. …”
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4
Daisy species classification based on image using Convolutional Neural Network algorithm / Haris Hidayatullah Khaimuza
Published 2024“…Second objective is to develop the prototype of daisy species classification based on image using CNN algorithm. The last objective is to evaluate the accuracy of CNN model in the daisy species classification based on image. …”
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5
Sentiment classification for malay newspaper using clonal selection algorithm / Nur Fitri Nabila Mohamad Nasir
Published 2013“…The experimental results show that our method can achieve better performance in clonal selection algorithm sentiment classification and the data collected cannot be used at once in this model because training data is very time-consuming if using all the data. …”
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6
Modified word representation vector based scalar weight for contextual text classification
Published 2024“…For this experiment, the modified word vectors serve as input to train a Machine Learning (ML) model for the text classification process, aiming for the developed ML model to have a significantly smaller parameter count. …”
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7
An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani
Published 2015“…The improved algorithm is constructed by adding new parameter and classification rule to existing algorithm. …”
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8
An Arabic hadith text classification model using convolutional neural network and support vector machine / Mohd Irwan Mazlin
Published 2022“…There are 6 different ways of designing the experiment to evaluate the result of the study, which are an experiment with the model using different stemming techniques, an experiment with the model using three different algorithms, the result analysis of confusion matric of three algorithms, experiment the model using different SVM kernel, experiment the model using unseen data, produce precision, recall, F1-measure and accuracy result of the model and parameter. …”
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9
Classification for large number of variables with two imbalanced groups
Published 2020“…Both algorithms are beneficial towards the practitioners of classification predictive modelling as well as statisticians in pattern recognition domain.…”
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10
Diagnosis and recommender system for diabetes patient using decision tree / Nurul Aida Mohd Zamary
Published 2024“…To evaluate the model, the model accuracy, precision, recall, F1- score, and confusion matrix were used. …”
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11
Diabetic Retinopathy Detection Model using Hybrid of U-Net and Vision Transformer Algorithms
Published 2024“…The usage of transformer architecture helps improve feature extraction and classification performance which ensures that our model captures all patterns in retinal images. We have evaluated our model on APTOS Blindness detection dataset in which our model outperforms traditional convolutional neural networks-based models. …”
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A Multi-tier Model and Filtering Approach to Detect Fake News Using Machine Learning Algorithms
Published 2024“…The consensus layer acts as the final decision when collision results occur in the first two-tier layer. The proposed model is applied to the WEKA software tool to test and evaluate the model from both datasets. …”
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13
Accuracy assessment of Digital Terrain Model (DTM) Constructed Cloth Simulation Filter (CSF) and Multi Curvature Classification (MCC) algorithm on UAV LiDAR dataset / Mohamad Khair...
Published 2023“…This study aims to evaluate the effectiveness of open-source software algorithms for ground classification in lidar point clouds and the subsequent generation of accurate DTMs. …”
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14
Text spam messages classification using Artificial Immune System (AIS) algorithms
Published 2024thesis::master thesis -
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Sentiment analysis using negative selection algorithm for Twitter’s messages / Nazirah Che Alhadi
Published 2012“…This project methodology consists of five phases which are preliminary study, data collection and preparation, model development, model evaluation and documentation. …”
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Crytojacking Classification based on Machine Learning Algorithm
Published 2024journal::journal article -
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Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer
Published 2017“…Furthermore, the Lazy-IBK algorithm have been validated to produce the best classifier model, with the machine learning algorithm performance of 65.26%, recall of 65.3%, and 65.4% F-measured as compared to other evaluated machine learning classifier algorithms proposed within the WEKA data mining algorithm. …”
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18
Recommendation System Model For Decision Making in the E-Commerce Application
Published 2024thesis::doctoral thesis -
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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak
Published 2019“…It involves development of Max-Min Rule-Based Classification Algorithm. The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. …”
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20
Comparison of Logistic Regression, Random Forest, SVM, KNN Algorithm for Water Quality Classification Based on Contaminant Parameters
Published 2024“…The purpose of this study is to evaluate and compare the performance of these algorithms in terms of accuracy. …”
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