Search Results - (( data optimization method algorithm ) OR ( data decision tree algorithm ))
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1
Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
Published 2020“…Decision tree is an important method in data mining to solve the classification problems. …”
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Enhanced dimensionality reduction methods for classifying malaria vector dataset using decision tree
Published 2021“…RNA-Seq data are utilized for biological applications and decision making for classification of genes. …”
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Modeling forest fires risk using spatial decision tree
Published 2011“…This paper presents our initial work in developing a spatial decision tree using the spatial ID3 algorithm and Spatial Join Index applied in the SCART (Spatial Classification and Regression Trees) algorithm. …”
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Application of Decision Trees in Athlete Selection: A Cart Algorithm Approach
Published 2023“…The focus of this study is on the use of DTs, employing the Classification and Regression Trees (CART) algorithm, in the initial screening of athletes. …”
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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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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. …”
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Real-Time State of Charge Estimation of Lithium-Ion Batteries Using Optimized Random Forest Regression Algorithm
Published 2024Subjects:Article -
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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Investigating optimal smartphone placement for identifying stairs movement using machine learning
Published 2023“…The data was trained against 6 machine learning algorithms namely Decision Tree, Logistic Regression, Naive Bayes, Random Forest, Neural Networks and KNN. …”
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Correlation analysis and predictive performance based on KNN and decision tree with augmented reality for nuclear primary cooling process / Ahmad Azhari Mohamad Nor
Published 2024“…Subsequently, predictive models employing k-nearest neighbour and decision tree algorithms are constructed and evaluated based on accuracy, precision, and recall metrics. …”
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Classification with degree of importance of attributes for stock market data mining
Published 2004“…We present another modification of fuzzy decision tree (FDT) classification techniques that aims to combine symbolic decision trees in data classification with approximate reasoning offered by fuzzy representation. …”
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A Data Mining Approach to Enhancing Birth and Death Registration Processes
Published 2025“…The apriori algorithm refines registration data by identifying associations that reduce inconsistencies, while decision three analysis highlights critical factors contributing to registrations delays. a total 45 decision trees were generated, leading to policy recommendation aimed at improving data collection and public compliance. …”
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A direct ensemble classifier for imbalanced multiclass learning
Published 2012“…A combiner method called OR-tree is used to combine the decisions obtained from the ensemble classifiers.The DECIML framework has been tested with several benchmark dataset and shows promising results.…”
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Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves
Published 2024“…In the next phase, the datasets are optimized using the Salp Swarm Algorithm (SSA), which improves classification accuracy. …”
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Classification of Diabetes Mellitus using Ensemble Algorithms
Published 2021“…The objective of this study is to perform DM classification using various machine learning algorithms. In this paper, individual classifiers such as Support Vector Machine, Naïve Bayes, Bayes Net, Decision Stump, k - Nearest Neighbors, Logistic Regression, Multilayer Perceptron and Decision Tree are experimented. …”
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Hybrid tabu search – strawberry algorithm for multidimensional knapsack problem
Published 2022“…The parameters setting to run the hybrid TS-SBA was determined by using a combination of Factorial Design of Experiments and Decision Tree Data Mining methods. Finally, the hybrid TS-SBA was evaluated using an MKP benchmark problem. …”
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Edge assisted crime prediction and evaluation framework for machine learning algorithms
Published 2022“…A maximum accuracy of 81% is obtained for Decision Tree algorithm during the prediction of crime. …”
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A conceptual framework for multi-objective optimization of building performance: Integrating intelligent algorithms, simulation tools, and climate adaptation
Published 2025“…Quantitative analysis highlights China’s prominent contributions to the field, while the thematic analysis reveals three key findings: (1) optimization methods based on intelligent algorithms such as NSGA-II, artificial neural networks, and gradient-boosted decision trees significantly enhance computational efficiency; (2) dynamic simulation integrated with lifecycle assessment enables a more comprehensive evaluation of building performance; and (3) climate-adaptive strategies improve building resilience to future climate uncertainties. …”
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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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Optimized techniques for landslide detection and characteristics using LiDAR data
Published 2018“…The locations of landslides were detected accurately by employing two Machine learning classifiers, namely, SVM and RF, decision rule and hierarchal rules sets were developed by applying decision tree (DT) algorithm to provide improved landslide inventory. …”
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