Search Results - (( _ relationship tree algorithm ) OR ( its application use algorithm ))

Laptop price prediction using decision tree algorithm / Nurnazifah Abd Mokti by Abd Mokti, Nurnazifah

“…This research project focuses on developing a laptop price prediction model using the decision tree algorithm based on laptop specifications. …”
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Predicting factor of online purchasing behaviour among university students in UiTMCT / Mohd Fadzlee Mazlan by Mazlan, Mohd Fadzlee

“…Several prediction rules already been produced with high interestingness by using K-Mean clustering algorithm and Random Tree algorithm. …”
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Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

“…However the predictive accuracy of SVM achieved by [2] in stock market is relatively lower than other classification applications [8, 9]. Also the existing relationship between the future stock returns and its accounting information, one would expect it to be a weak relationship. …”
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A decision tree based on spatial relationships for predicting hotspots in peatlands by Sitanggang, Imas Sukaesih, Yaakob, Razali, Mustapha, Norwati, Nuruddin, Ahmad Ainuddin

“…This work applied a spatial decision tree algorithm on spatial data of forest fires. The algorithm is the improvement of the conventional decision tree algorithm in which the distance and topological relationships are included to grow up spatial decision trees. …”
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Attribute related methods for improvement of ID3 Algorithm in classification of data: A review by Nur Farahaina, Idris, Mohd Arfian, Ismail

“…There are several learning algorithms to implement the decision tree but the most commonly-used is ID3 algorithm. …”
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Driver behaviour classification: a research using OBD-II data and machine learning by Muhamad Fadzil, Nur Farisya Aqilah, Mohd Fadzir, Hilda, Mansor, Hafizah, Rahardja, Untung

“…Then, the proposed model makes use of the K-Means algorithm to create driving behaviour labels whether belong to safe or aggressive - validated by the safety score criteria. …”
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Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor by Adilah, Abdul Ghapor

“…As for the multiple outliers, a clustering algorithm is considered and a dendogram to visualise the clustering algorithm is used. …”
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Using unique-prime-factorization theorem to mine frequent patterns without generating tree by Tohidi, Hossein, Ibrahim, Hamidah

“…In this study we introduce an algorithm to generate frequent patterns without generating a tree and therefore improve the time complexity and memory complexity as well. …”
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Accuracy and performance analysis for classification algorithms based on biomedical datasets by Al-Hameli, Bassam Abdo, Alsewari, Abdulrahman A., Khubrani, Mousa, Fakhreldin, Mohammoud

“…Trees based Decision Tree (ID3) algorithm, Bayesian Theorem based Hidden Naïve Bayes (HNB) algorithm. …”
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Employing Genetic Algorithm to Construct Epigenetic Tree-Based Features for Enhancer Region Prediction by Lee, Nung Kion, Mohd Tajuddin, Abdullah, Pui, Kwan Fong

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Phylogenetic relationships of Malaysian monkeys, Cercopithecidae, based on mitochondrial cytochrome c sequences by Md-Zain, B.M., Mohamad, M., Ernie-Muneerah, M.A., Ampeng, A., Jasmi, A., Lakim, M., Mahani, M.C.

“…In addition, tree topologies indicate a good resolution of the Colobinae phylogenetic relationships at the intergeneric level, but with low bootstrap support. …”
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Delineating mangrove forest zone using spectral reflectance by Abdul Whab @ Abdul Wahab,, Zulfa

“…Species identification with spectral library derived from in-situ measurements using SID algorithm and derived from Landsat 8 using SAM algorithm was done. …”
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Footwear quality evaluation using decision tree and logistic regression models by Tan, Swee Choon

“…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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State of charge estimation for electric vehicles using random forest by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

“…By leveraging decision trees and ensemble learning, the RF model forms resilient relationships between input parameters, such as voltage, current, ambient temperature, and battery temperatures, and SOC values. …”
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An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA by Bian, Hui

“…Traditional machine learning algorithms, such as Decision Trees, Naive Bayes, Random Forest, Random Trees, Multi-Layer Perceptron, and Support Vector Machines, have been extensively applied to address these threats. …”
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Seeing trees from space: above-ground biomass estimates of intact and degraded montane rainforests from high-resolution optical imagery by Phua, Mui How, Ling, Zia-Yiing, David Anthony Coomes, Wilson Wong, Alexius Korom, Satoshi Tsuyuki, Keiko Ioki, Yasumasa Hirata, Hideki Saito, Gen Takao

“…To this purpose, preprocessed IKONOS imagery was segmented using a watershed algorithm; stem diameter values were then estimated from the cross-sectional crown areas of these trees using regression relationships obtained from ground-based measurements. …”
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Reverse migration prediction model based on machine learning / Azreen Anuar by Anuar, Azreen

“…For this purpose, three (3) algorithms have been assessed, namely, the Random Forest, Decision Tree, and Gradient Boosted Tree. …”
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Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari by Satari, Siti Zanariah

“…Here, we introduce a measure of similarity based on the circular distance and obtain a cluster tree using the single linkage clustering algorithm. …”
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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 by Althuwaynee, Omar F., Pradhan, Biswajeet, Park, Hyuck Jin, Lee, Jung Hyun

“…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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Application of machine learning algorithms to predict removal efficiency in treating produced water via gas hydrate-based desalination by Nallakukkala, Sirisha, Tackie-Otoo, Bennet Nii, Aliyu, Ruwaida, Lal, Bhajan, Nallakukkala, Jagadish Ram Deepak, Devi, Gayathri

“…In this context. ML algorithms provide powerful data driven means to model complex relationship within experimental datasets to improve process optimisation This study systematically evaluated several supervised ML models, including Random Forest (RF) Support Vector Machines (SVM), Ridge Regression, Lasso Regression, Decision Tree, Extra Tree Regression, Gradient Boost, and XGBoost, to predict removal efficiency in GHBD system. …”
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