Search Results - (( model validation _ algorithm ) OR ( mining classification using algorithms ))
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1
Data Mining Analysis Of Chronic Kidney Disease (CKD) Level
Published 2022“…Adding the uncertain class the best accuracy obtained was 98.5% using the SMO algorithm. A predictive classification model that determines the accuracy for three classification classes was developed accordingly using the SMO algorithm.…”
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Monograph -
2
Analysis Of Failure In Offline English Alphabet Recognition With Data Mining Approach
Published 2019“…Classification analysis was initially performed on all seven classifier’s algorithms at 10-fold dross validation mode. …”
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Monograph -
3
Improvement of fuzzy neural network using mine blast algorithm for classification of Malaysian Small Medium Enterprises based on strength
Published 2015“…The ANFIS optimized by AMBA is used employed to model classification of Malaysian small medium enterprises (SMEs) based on strength using non-financial factors. …”
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Thesis -
4
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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5
Hybrid ant colony optimization and genetic algorithm for rule induction
Published 2020“…The performance of the proposed classifier was tested against other existing hybrid ant-mining classification algorithms namely, ACO/SA and ACO/PSO2 using classification accuracy, the number of discovered rules and model complexity. …”
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Article -
6
An Automated System For Classifying Conference Papers
Published 2021“…A randomised stratified 5- fold cross validation was then applied on several data mining algorithms and evaluated using the F-measure as a metric. …”
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Final Year Project / Dissertation / Thesis -
7
Integrated approach using data mining-based decision tree and object-based image analysis for high-resolution urban mapping of WorldView-2 satellite sensor data
Published 2016“…Many features were explored by using a DM algorithm, which created the classification rules as a decision tree (DT) structure from the first study area. …”
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8
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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AN AGENT-BASED DOCUMENT CLASSIFICATION MODEL TO IMPROVE THE EFFICIENCY OF THE AUTOMATED SYSTEMATIC REVIEW PROCESS
Published 2023“…Firstly, the document classification algorithm analyses a full text of research articles and evaluates relevancy. …”
Review -
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A Predictive Classification Model For Running Injury
Published 2022“…The J48, SMO, Random Forest, and Simple Logistic algorithms were used for 10-fold cross validation mode classification benchmarked on the ZeroR baseline algorithm. …”
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Monograph -
11
Enhanced dimensionality reduction methods for classifying malaria vector dataset using decision tree
Published 2021“…A feature ranking and earlier experience are used. The performances of the model are evaluated and validated using the classification accuracy to compare existing approaches in the literature. …”
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12
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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Thesis -
13
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 -
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Mining The Basic Reproduction Number (R0) Forecast For The Covid Outbreak
Published 2022“…The COVID-19 Basic Reproduction Number, R0 a predictive model is developed using a linear regression classification algorithm to predict the COVID-19 Basic Reproduction Number, Robased on the actual COVID-19 Basic Reproduction Number, R0. …”
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Monograph -
16
Activity recognition based on accelerometer sensor using combinational classifiers
Published 2015“…The result of classification was validated using 10-fold cross validation algorithm in order to make sure all the experiments perform well.…”
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Conference or Workshop Item -
17
Integration of object-based image analysis and data mining techniques for detailes urban mapping using remote sensing
Published 2015“…This algorithm represents the decision tree knowledge model, enables fast classification of intra-urban classes, and disables subjectivities related to the interaction with analysts. …”
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18
Predicting heart disease using ant colony optimization / Siti Aisyah Ismail
Published 2021“…They have to make more effort to detect heart disease, but it is not an easy task. Thus, this study used the Ant Colony Optimization algorithm with data mining called Ant-Miner to predict heart disease because it is said that Ant-Miner’s rule list is simpler than other rule induction algorithms. …”
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Student Project -
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Prediction of breast cancer relapse time in continuous scale based on type-2 TSK fuzzy model
Published 2010“…In the first objective of the thesis, a lemma has been proven and a new hybrid algorithm based on Fuzzy Association Rule Mining has been proposed to gather some selected genes and generate fuzzy rules for classification. …”
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20
Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi
Published 2019“…Experiments demonstrate and prove that the proposed EBPSO method produces better accuracy mining data and selecting subset of relevant features comparing other algorithms. …”
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