Search Results - (( variables classification techniques algorithm ) OR ( using optimization based algorithm ))
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1
A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification
Published 2023“…The performance of the proposed SCSO algorithm was compared with six state-of-the-art and recent wrapper-based optimization algorithms using the validation metrics of classification accuracy, optimum feature size, and computational cost in seconds. …”
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Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…The accuracy of each algorithm was evaluated using LibSVM, Bayes network, and Adaboost classifier. …”
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Thesis -
3
A novel ensemble decision tree-based CHi-squared Automatic Interaction Detection (CHAID) and multivariate logistic regression models in landslide susceptibility mapping
Published 2014“…An ensemble algorithm of data mining decision tree (DT)-based CHi-squared Automatic Interaction Detection (CHAID) is widely used for prediction analysis in variety of applications. …”
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4
Chemometrics analysis for the detection of dental caries via ultraviolet absorption spectroscopy / Katrul Nadia Basri
Published 2023“…Dimension reduction algorithm such as LDA and CNN were applied on the spectra to reduce the number of variables to be trained. …”
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5
Flash floods prediction using real time data: an implementation of ANN-PSO with less false alarm
Published 2019“…The results include flood probabilities and prediction analysis using proposed algorithm.…”
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Proceeding Paper -
6
Development of biosignals-based multimodal biometric system
Published 2014“…The best performance of the work is based on simple-sum score fusion with a piecewiselinear normalization technique which provides an EER of 0. 7%.…”
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7
Classification of tropical rainforest using different classification algorithm based on remote sensing imagery: A study of Gunung Basor
Published 2019“…Remote sensing technologies are used globally to derive some of crucial spatial variable parameter such as vegetation cover. Three different classification algorithm, minimum distance classifier, Mahalanobis distance classifier and maximum likelihood algorithm was applied to classify the forest area in Gunung Basor. …”
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Undergraduate Final Project Report -
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Feature Ranking Techniques For 3D ATS Drug Molecular Structure Identification
Published 2018“…The first phase is to carry out a thorough analysis of the effectiveness and capability of various feature ranking techniques in ATS drug identification. Six feature ranking techniques were used: Information Gain (IG), Gain Ratio (GR), Symmetrical Uncertainty (SU), Support vector machine based recursive feature elimination (SVM-RFE), and Variable Importance based random forest (VI-RF). …”
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9
Hybrid ACO and SVM algorithm for pattern classification
Published 2013“…The average classification accuracies for the ACOR-SVM, IACOR-SVM, ACOMV-R and IACOMV-R algorithms are 94.73%, 95.86%, 97.37% and 98.1% respectively. …”
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10
Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification
Published 2020“…However, its precision affected by numerous factors like data set type, spatial resolution, number of variables, etc. The overall objective of this study is to explore some factors affecting non- parametric LCM classification techniques in terms of accuracy assessment and to compare their performance with a well-established classification technique by implementing Landsat 8 and Sentinel satellites. …”
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11
Mixed variable ant colony optimization technique for feature subset selection and model selection
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A hybrid-based modified adaptive fuzzy inference engine for pattern classification
Published 2011“…A modified Apriori algorithm technique is utilized to reduce a minimal set of decision rules based on input output data set. …”
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Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms
Published 2024“…The classification algorithm used in this research is the Convolutional Neural Network (CNN) algorithm. …”
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15
Finding an effective classification technique to develop a software team composition model
Published 2017“…Ineffective software team composition has become recognized as a prominent aspect of software project failures.Reports from results extracted from different theoretical personality models have produced contradicting fits, validity challenges, and missing guidance during software development personnel selection.It is also believed that the technique/s used while developing a model can impact the overall results.Thus, this study aims to: 1) discover an effective classification technique to solve the problem, and 2) develop a model for composition of the software development team.The model developed was composed of three predictors: team role, personality types, and gender variables; it also contained one outcome: team performance variable.The techniques used for model development were logistic regression, decision tree, and Rough Sets Theory (RST).Higher prediction accuracy and reduced patte rn complexity were the two parameters forselecting the effective technique.Based on the results, the Johnson Algorithm (JA) of RST appeared to be an effective technique for a team composition model.The study has proposed a set of 24 decision rules for finding effective team members.These rules involve gender classification to highlight the appropriate personality profile for software developers.In the end, this study concludes that selecting an appropriate classification technique is one of the most important factors in developing effective models.…”
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Finding an effective classification technique to develop a software team composition model
Published 2018“…In the end, this study concludes that selecting an appropriate classification technique is one of the most important factors in developing effective models. …”
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Finding an effective classification technique to develop a software team composition model
Published 2018“…In the end, this study concludes that selecting an appropriate classification technique is one of the most important factors in developing effective models. …”
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18
An improved directed random walk framework for cancer classification using gene expression data
Published 2020“…Numerous cancer studies have combined different machine learning techniques for the cancer diagnosis to improve the accuracy of cancer classification. …”
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Thesis -
19
Integrated ACOR/IACOMV-R-SVM Algorithm
Published 2017“…Support Vector Machine (SVM), which originates from the statistical approach, is a present day classification technique. The main problems of SVM are selecting feature subset and tuning the parameters. …”
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Gene Selection For Cancer Classification Based On Xgboost Classifier
Published 2022“…XGBoost Classifier is applied in this research, which it is an efficient open-source implementation of the gradient boosted trees algorithm. Gradient boosting is a supervised learning algorithm, which attempts to accurately predict a target variable by combining the estimates of a set of simplifier, weaker models. …”
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Undergraduates Project Papers
