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Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
Published 2020“…There are several learning algorithms to implement the decision tree but the most commonly-used is ID3 algorithm. …”
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2
Hyper-Heuristic Evolutionary Approach for Constructing Decision Tree Classifiers
Published 2021“…Finding optimal values for the hyper parameters of a decision tree construction algorithm is a challenging issue. …”
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3
Photogrammetric unmanned aerial vehicle for digital terrain model estimation under oil palm tree canopy area / Suzanah Abdullah
Published 2021“…It was found that WS algorithm recorded the lower RMSE value of 2.824m at 40m flying height, IWS algorithm obtained a lower RMSE value of 2.879m at 80m flying height, OBIA and SG algorithms obtained a lower RMSE value of 2.246m and 2.182m respectively at 100m flying height. …”
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Thesis -
4
Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd
Published 2022“…ID3 has the most advantages among the three algorithms, especially in processing time, as it builds the fastest tree with short depth. …”
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5
Partial Binary Tree Network (Pbtn): A New Dynamic Element Matching (Dem) Approach To Current Steering Digital Analog Converter (Dac)
Published 2014“…In this research, a new DEM algorithm is proposed on Current-Steering DACs with Partial Binary Tree Network (PBTN) algorithm to overcome glitches transitions with low complexity. …”
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6
A comparison of support vector machine and decision tree classifications using satellite data of Langkawi Island
Published 2009“…Two classifiers were used to classify SPOT 5 satellite image; Decision Tree (DT) and Support Vector Machine (SVM). The Decision Tree rules were developed manually based on Normalized Difference Vegetation Index (NDVI) and Brightness Value (BV) variables. …”
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7
Optimizing tree planting areas through integer programming and improved genetic algorithm
Published 2012“…Meanwhile, the improvement in Genetic Algorithm is focused on the strategies of specific random value, deterministic crossover and deterministic mutation. …”
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8
An Integrated Principal Component Analysis And Weighted Apriori-T Algorithm For Imbalanced Data Root Cause Analysis
Published 2016“…In conclusion, the proposed algorithm is able to overcome the rare item issue by implementing covariance based support value normalization and high computational costs issue by implementing indexing enumeration tree structure.Future work of this study should focus on rule interpretation to generate more human understandable rule by novice in data mining. …”
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9
Comparison Of Phylogenetic Trees Using Difference Distance Function Method
Published 2005“…The pre-processing is implemented using the Microsoft Visual C++. The phylogenetic tree is build using the PHYLlP (the PHYlogeny Inference Package), a package of programs for inferring phylogenies (evolutionary trees). …”
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Final Year Project Report / IMRAD -
10
Case Slicing Technique for Feature Selection
Published 2004“…The classification accuracy obtained from the CST method is compared to other selected classification methods such as Value Difference Metric (VDM), Pre-Category Feature Importance (PCF), Cross-Category Feature Importance (CCF), Instance-Based Algorithm (IB4), Decision Tree Algorithms such as Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5), Rough Set methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) and Neural Network methods such as the Multilayer method.…”
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11
Crown counting and mapping of missing oil palm tree using airborne imaging system
Published 2019“…A graphical user interface by using MATLAB language was created based on the best executed method to aid users in counting the trees automatically. This helps to facilitate semi-skillful users to implement the tree counting algorithms. …”
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12
Investigation Of Electrical Capacitance Tomography For Agarwood Detection
Published 2022“…In short, for agarwood different size (MSSIM value = 0.1052), agarwood different position (top right) (MSSIM value = 0.1587) and agarwood phantom F (MSSIM value = 0.1081) were the reconstructed image that closely matches with the reference image because the MSSIM value ranges is between 0 to 1, whereby the value 1 means the perfect match of the reconstructed image with the original one.…”
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Undergraduates Project Papers -
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Improved random forest for feature selection in writer identification
Published 2015“…While Mean Absolute Error (MAE) values use to identify the variance between writers, VI value was used for splitting process in tree and MAE value is to ensure the intra-class (same writer) invariance is lower than inter-class (different writer) invariance because lower intra-class invariance indicates accuracy to the real author. …”
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15
Lightning fault classification for transmission line using support vector machine
Published 2023“…The classification performance of the developed algorithms was evaluated using confusion matrix. Overall, SVM algorithm performed better than k-NN in terms of classification accuracy, achieving a value of 97.10% compared to k-NN’s 70.60%. …”
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Conference or Workshop Item -
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Lightning Fault Classification for Transmission Line Using Support Vector Machine
Published 2024“…The classification performance of the developed algorithms was evaluated using confusion matrix. Overall, SVM algorithm performed better than k-NN in terms of classification accuracy, achieving a value of 97.10% compared to k-NN's 70.60%. …”
Conference Paper -
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Water optimization technique for precision irrigation system using IoT and machine learning
Published 2022“…After implementation of proposed work, for single banana tree 31.4 of the water requirement has been optimized in 2020 time period. …”
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Hardware development of autonomous mobile robot based on actuating lidar
Published 2022“…From here, the extracted values are implied on k-NN, Decision Tree and CNN training algorithm. …”
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Car dealership web application
Published 2022“…Tree SHAP, which was implemented by third-party SHAP Python library, were used in model monitoring and made the models interpretable. …”
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Final Year Project / Dissertation / Thesis -
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Analysis of hyperspectral reflectance for disease classification of soybean frogeye leaf spot using Knime analytics
Published 2023“…This analysis involved the implementation of machine learning (ML) algorithms, including decision trees, random forests, and stacking, to classify soybean FLS severity levels. …”
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