Search Results - (( developing function method algorithm ) OR ( data classification tree algorithm ))
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1
Tree-based contrast subspace mining method
Published 2020“…The research works involve first preparing the real world numerical and categorical data sets. Then, the tree-based method, the genetic algorithm based parameter values identification of tree-based method, and followed by the genetic algorithm based tree-based method, for numerical data sets are developed and evaluated. …”
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Thesis -
2
A comparison of support vector machine and decision tree classifications using satellite data of Langkawi Island
Published 2009“…The study indicates that the classification accuracy of SVM algorithm was better than DT algorithm. The overall accuracy of the SVM using four kernel types was above 73% and the overall accuracy of the DT method was 69%. …”
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3
Optimized tree-classification algorithm for classification of protein sequences
Published 2016“…In this work, we have proposed an optimized tree-classification technique which uses cluster k nearest neighbor classification algorithm to classify protein sequences into superfamilies. …”
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4
Optimized tree-classification algorithm for classification of protein sequences
Published 2016“…In this work, we have proposed an optimized tree-classification technique which uses cluster k nearest neighbor classification algorithm to classify protein sequences into superfamilies. …”
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5
A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…There are two methods in dealing with imbalanced classification problem, which are based on data or algorithmic level. …”
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6
New Learning Models for Generating Classification Rules Based on Rough Set Approach
Published 2000“…Also, the proposed models for learning in data sets generated the classification rules faster than other methods. …”
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7
Image classification using two dimensional wavelet coefficients with parallel computing
Published 2020“…This research algorithm demonstrated a very promising result with Support Vector Machines, this algorithm produces a 90% of accuracies whereas the decision tree algorithm gets 100% accuracies. …”
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Final Year Project / Dissertation / Thesis -
8
Data Analysis and Rating Prediction on Google Play Store Using Data-Mining Techniques
Published 2022“…This biggest Android Application (App) provides a wide variety of details on requirements such as reviews, quality, number of installs, and explanations for device functionality. This study aims to predict the ratings of Google Play Store apps using decision trees for classification in machine learning algorithms. …”
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9
Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification
Published 2020“…The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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10
An efficient computational intelligence technique for classification of protein sequences
Published 2014“…The technique has considered the occurrence frequency of each amino acid in a sequence. Popular classification algorithms such as decision tree, naive Bayes, neural network, random forest and support vector machine have been employed to evaluate the effectiveness of the encoding method utilized in the proposed framework. …”
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11
Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…Then, the classifier (support vector machine (SVM) and data mining (DM) algorithm, decision tree (DT) were applied on each fusion image and their accuracy were evaluated. …”
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12
A study on component-based technology for development of complex bioinformatics software
Published 2004“…Othman proposed a clustering algorithm named BTreeBicluster. The BTreeBicluster starts with the development of GO tree and enriching it with expression similarity from the Sacchromyces genes. …”
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Monograph -
13
Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data
Published 2018“…Random Forests (RF) are ensemble of trees methods widely used for data prediction, interpretation and variable selection purposes. …”
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14
Landslide susceptibility mapping using decision-tree based chi-squared automatic interaction detection (CHAID) and logistic regression (LR) integration
Published 2014“…This new algorithm was developed to overcome the subjectivity of the manual categorization of scale data of landslide conditioning factors, and to predict rainfall-induced susceptibility map in Kuala Lumpur city and surrounding areas using geographic information system (GIS). …”
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15
Power line corridor vegetation encroachment detection from satellite images using retinanet and support vector machine
Published 2023“…Also, a corridor extraction algorithm has been developed to extract the region of interest (ROI) around the transmission towers. …”
text::Thesis -
16
Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd
Published 2022“…The study verified that the FID3-DBD algorithm could classify the continuous data, and the BFID3-DBD algorithm overcame the overfitting issue, reduced high variance, and increased test data classification accuracy.…”
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17
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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Article -
18
Terahertz sensing analysis for early detection of ganoderma boninense disease using near infrared (NIR) spectrometer
Published 2023“…Ergosterol can be used as a biomarker for the detection of G. boninense since it can only be found in the fungal-infested plant. In classification, four different ML algorithms: K-Nearest Neighbour (kNN), Naïve Bayes (NB), Support Vector Machine (SVM) and Decision Tree (DT) are tested to classify healthy and infected oil palm samples. …”
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19
Phylogenetic tree classification system using machine learning algorithm
Published 2015“…A study is conducted to develop an automated phylogenetic tree image classification system by using machine learning algorithm. …”
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Final Year Project Report / IMRAD -
20
Drone-based surveillance of palm tress ecosystems
Published 2024“…The study aims to improve the accuracy and efficiency of palm health detection by integrating MATLAB's initial object recognition with advanced deep learning algorithms. The initial phase of the research focuses on elucidating the challenges associated with detecting palm tree health issues using conventional image processing methods in MATLAB. …”
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