Search Results - (( java application customization algorithm ) OR ( based observational tree algorithm ))
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1
Improvement on agglomerative hierarchical clustering algorithm based on tree data structure with bidirectional approach
Published 2024Conference Paper -
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Improved Boosting Algorithms by Pre-Pruning and Associative Rule Mining on Decision Trees for predicting Obstructive Sleep Apnea
Published 2017“…The Pruned-Associative-Rule-Mined Decision Trees (PARM-DT) developed by adopting pre-pruning techniques on tree depth, minimum leaf and/or parent node size observations and maximum number of tree splits, based on Apriori and/or Adaptive Apriori (AA) frameworks, is boosted to achieve better predictive accuracies. …”
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3
Prediction of earnings manipulation on Malaysian listed firms: A comparison between linear and tree-based machine learning
Published 2021“…Thus, the aim of the paper is to compare the earnings manipulation prediction models developed by using two types of machine learning algorithms; linear and tree categories. The linear based machine learning are Logistic Regression and Generalized Linear Model while the tree based are Decision Tree and Random Forest. …”
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Decision tree-based approach for online management of PEM fuel cells for residential application
Published 2004“…A database is extracted from a previously-performed Genetic Algorithm (GA)-based optimization has been used to create a suitable decision tree, which was intended for generalizing the optimization results. …”
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5
Algorithm of the longest commonly consecutive word for plagiarism detection in text based document
Published 2008“…Based on the experiment, the proposed algorithm outperforms the suffix tree in the length of observed paragraph below one hundred words.…”
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Decision tree-based approach for online management of pem fuel cells for residential application
Published 2004“…A database was extracted from a previously�performed Genetic Algorithm (GA)-based optimization that has been used to create a suitable decision tree, which was intended for generalizing the optimization results. …”
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7
Algorithm Development of Bidirectional Agglomerative Hierarchical Clustering Using AVL Tree with Visualization
Published 2024thesis::doctoral thesis -
8
Delineating mangrove forest zone using spectral reflectance
Published 2020“…Overall, the spectral reflectance measurement pairing with leaf chlorophyll measurement provides a sound basis for classifying mangrove tree species (R2>80%). Mangrove loss resulting from anthropogenic activities was observed across the study area. …”
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9
Hybridization of SLIC and extra tree for object based image analysis in extracting shoreline from medium resolution satellite images
Published 2018“…Thus, the object-based approach is proposed using a combination of segmentation algorithms, namely Felzenswalb, Quickshift, and SLIC, together with 15 machine learning classifiers, to classify segmented images of Langkawi Island. …”
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Footwear quality evaluation using decision tree and logistic regression models
Published 2022“…The analysis showed that Decision Tree with Gini algorithm (three branches) in the first method prevails against the other methods with misclassification rate of 0.1307. …”
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12
Edge assisted crime prediction and evaluation framework for machine learning algorithms
Published 2022“…As a result, in this paper, a strategy is provided for predicting crime occurrences in a city based on historical events and demographic observation. …”
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Water optimization technique for precision irrigation system using IoT and machine learning
Published 2022“…The GBT is used to predict the real values based on the observations. The LSTM is used to predict, time series prediction using different observations of the surrounding. …”
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14
Prediction of Heart Disease Risk Using Machine Learning with Correlation-based Feature Selection and Optimization Techniques
Published 2021“…Numerous machine learning classifiers, Decision Tree, Discriminant Analysis, Logistic Regression, Naïve Bayes, Support Vector Machines, k-Nearest Neighbors, Bagged Trees, Optimizable Tree, and Optimizable k-Nearest Neighbors are trained using 10-fold cross-validation for efficient heart disease risk prediction on the Correlation-based Feature Selection optimal set of the integrated heart dataset. …”
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15
Tree species and aboveground biomass estimation using machine learning, hyperspectral and LiDAR data / Nik Ahmad Faris Nik Effendi
Published 2022“…In this research, Object-Based Image Analysis (OBIA) method was applied on hyperspectral data to extract the crown of individual tree species for classification and estimation purposes. …”
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16
Enhancing obfuscation technique for protecting source code against software reverse engineering
Published 2019“…The proposed technique can be enhanced in the future to protect games applications and mobile applications that are developed by java; it can improve the software development industry. …”
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17
Detecting Malware with Classification Machine Learning Techniques
Published 2023“…The study assesses the effectiveness of several algorithms, including Naïve Bayes, Support Vector Machine (SVM), KNearest Neighbor (KNN), Decision Tree, Random Forest, and Logistic Regression, through an examination of a publicly accessible dataset featuring both benign files and malware. …”
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Detecting Malware with Classification Machine Learning Techniques
Published 2023“…The study assesses the effectiveness of several algorithms, including Naïve Bayes, Support Vector Machine (SVM), KNearest Neighbor (KNN), Decision Tree, Random Forest, and Logistic Regression, through an examination of a publicly accessible dataset featuring both benign files and malware. …”
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The impact of fuzzy discretization�s output on classification accuracy of random forest classifier
Published 2020“…However, there are many different opinions on whether there is a need to perform discretization in data pre-processing for tree-based classifiers such as J48, Decision Tree and Random Forest. …”
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An IoT based system for magnify air pollution monitoring and prognosis using hybrid artificial intelligence technique
Published 2022“…The hypothesized artificial intelligence models are evaluated to the Root Mean Squares Error, Mean Squared Error and Mean absolute error, depending upon the performance measurements and a lower error value model is chosen. Based on the algorithm of the Artificial Intelligent System, the level of 5 air pollutants like CO2, SO2, NO2, PM 2.5 and PM10 can be predicted immediately by integrating the observations with errors. …”
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