Search Results - (( its classification modeling algorithm ) OR ( java application testing algorithm ))
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1
Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…EM and K-means clustering algorithms are used to cluster the multi-class classification attribute according to its relevance criteria and afterward, the clustered attributes are classified using an ensemble random forest classifier model. …”
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Article -
2
RSA Encryption & Decryption using JAVA
Published 2006“…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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Final Year Project -
3
Classification model for water quality using machine learning techniques
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Article -
4
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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Thesis -
5
Support directional shifting vector: A direction based machine learning classifier
Published 2021“…In order to justify the acceptability of this method, we have implemented this model on three different standard datasets. The model showed comparable accuracy with the existing standard supervised classification algorithm.…”
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6
An efficient AdaBoost algorithm for enhancing skin cancer detection and classification
Published 2024“…To improve accuracy, the AdaBoost algorithm is utilized, which amalgamates weak classification models into a robust classifier with high accuracy. …”
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7
Next generation insect taxonomic classification by comparing different deep learning algorithms
Published 2022“…The results show that different taxonomic ranks require different deep learning (DL) algorithms to generate high-performance models, which indicates that the design of an automated systematic classification pipeline requires the integration of different algorithms. …”
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8
Training functional link neural network with ant lion optimizer
Published 2020“…The result of the classification made by FLNN-ALO is compared with the standard FLNN model to examine whether the ALO learning algorithm is capable of training the FLNN network and improve its performance. …”
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Conference or Workshop Item -
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Intent-IQ: customer’s reviews intent recognition using random forest algorithm
Published 2025“…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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10
Mobile machine vision for railway surveillance system using deep learning algorithm
Published 2021“…In order to overcome this issue, machine vision embedded with deep learning algorithm can be implemented. Obstacle detection can be achieved through vision-based object detection, where the object classification model computes the images similarity to its respective classes, classifying its potential as an obstacle. …”
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Proceedings -
11
An extended oversampling method for imbalanced Quranic text classification based on a genetic algorithm
Published 2023“…However, the process of Quranic text classification is not without its challenges. One of the significant challenges in Quranic text classification is obtaining a homogenous and balanced dataset to train the classification models accurately. …”
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12
Loan Eligibility Classification Using Machine Learning Approach
Published 2023“…The performance of the models was compared to identify the most effective algorithm for loan eligibility classification. …”
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Undergraduates Project Papers -
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Combining object-based classification and data mining algorithm to classify urban surface materials from worldview-2 satellite image
Published 2014“…This algorithm provides a decision tree output to represent the knowledge model, enabled a faster classification of intra-urban classes, and disabled the subjectivities which are related to the interaction of the analyst. …”
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Conference or Workshop Item -
14
Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier
Published 2013“…In order to enhance SVM performance, these problems must be solved simultaneously because error produced from the feature subset selection phase will affect the values of the SVM parameters and resulted in low classification accuracy.Most approaches related with solving SVM model selection problem will discretize the continuous value of SVM parameters which will influence its performance.Incremental Mixed Variable Ant Colony Optimization (IACOMV) has the ability to solve SVM model selection problem without discretising the continuous values and simultaneously solve the two problems.This paper presents an algorithm that integrates IACOMV and SVM.Ten datasets from UCI were used to evaluate the performance of the proposed algorithm.Results showed that the proposed algorithm can enhance the classification accuracy with small number of features.…”
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Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application
Published 2020“…Performance Testing is used to test the performance of algorithm implementations in applications. …”
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Journal -
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Crytojacking Classification based on Machine Learning Algorithm
Published 2024journal::journal article -
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Classification of Google Play application using decision tree algorithm on sentiment analysis of text reviews / Aqil Khairy Hamsani, Ummu Fatihah Mohd Bahrin and Wan Dorishah Wan A...
Published 2023“…To achieve these objectives, the methods employed involve data preprocessing and implementing the Decision Tree (DT) algorithm for classification. The classification model is trained and tested using various split ratios, and the optimal depth for the DT is determined through parameter tuning to achieve the best accuracy. …”
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Sentiment analysis regarding marital issues using Naive Bayes algorithm / Farah Nabila Mohd Razali
Published 2025“…The results indicate that financial instability and poor communication are the most prevalent issues, with the overall sentiment being predominantly negative. The model's performance was evaluated using accuracy, precision, recall, and F1-score, demonstrating its reliability in sentiment classification. …”
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Thesis -
19
Classification of Citrus (Rutaceae) by Using Image Processing
Published 2019“…A machine learning algorithms, SVM have been used to build species identification models. …”
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Undergraduate Final Project Report -
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