Search Results - (( java segmentation using algorithm ) OR ( programming values tree algorithm ))
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1
Image clustering comparison of two color segmentation techniques
Published 2010“…Finally, the algorithm found, which would solve the image segmentation problem.…”
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2
Building customer churn prediction models in Indonesian telecommunication company using decision tree algorithm
Published 2023“…This decision tree model has an accuracy value of 78.28% with 19,6% customer churn rate. …”
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Optimizing tree planting areas through integer programming and improved genetic algorithm
Published 2012“…Therefore, a hybrid algorithm through an incorporation of Integer Programming and Improved Genetic Algorithm was proposed for planting lining design. …”
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4
Automatic Number Plate Recognition on android platform: With some Java code excerpts
Published 2016“…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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5
Development of seven segment display recognition using TensorFlow on Raspberry Pi
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Comparison Of Phylogenetic Trees Using Difference Distance Function Method
Published 2005“…PHYLIP contains program for reconstructing trees from distance matrices. …”
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Final Year Project Report / IMRAD -
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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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8
Prime-based method for interactive mining of frequent patterns
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9
Lightning fault classification for transmission line using support vector machine
Published 2023“…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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10
Lightning Fault Classification for Transmission Line Using Support Vector Machine
Published 2024“…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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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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Optimizing the carbon absorption of palm oil plantation in Negeri Sembilan / Hannis Syazani Zulkefle, Nur Nazirah Mohd Nazri and Nur Shahirah Mohd Shafie
Published 2019“…Data was collected from Malaysian Palm Oil Board (MPOB). The Simplex Algorithm in Linear Programming Method using QM for Windows is applied to find the solution. …”
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Automatic extraction of digital terrain model and Building Footprint from airborne LiDAR data using rule-based learning techniques
Published 2021“…Based on the results, the RMSE value are ±0.62 meter for the urban and ±0.28 meter for rural buildings footprints. …”
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Random Amplified Polymorphic DNA Analysis of Four Breeds of Sheep in Malaysia
Published 1999“…Genetic distance between populations ranged from 0.1040 to 0.1357 based on the Dice's algorithm while the distance based on the Jaccard's algorithm ranged from 0.1875 to 0.2381. …”
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18
Propositional satisfiability method in rough classification modeling for data mining
Published 2002“…Two models, Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) to represent the minimal reduct computation problem were proposed. …”
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