Search Results - (( java application using algorithm ) OR ( using factor ((model algorithm) OR (tree algorithm)) ))

A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

“…This thesis describes original research in the field of software quality model by presenting a Feature Ranking Algorithm (FRA) for Pragmatic Quality Factor (PQF) model. …”
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Reinforcement Learning Algorithm for Optimising Durian Irrigation Systems: Maximising Growth and Water Efficiency by Ramli, Muhammad Shahrul Azwan, Zainal Abidin, Mohamad Shukri, Hasan, Nor Shahida, Md Reba, Mohd Nadzri, Kolawole, Keshinro Kazeem, Ardiansyah, Rizqi Andry, Mpuhus, Sikudhan Lucas

“…The algorithm was developed by calibrating the AQUACROP model using data from actual durian plantations where rain-fed irrigation (rain-fed) was practised. …”
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Building customer churn prediction models in Indonesian telecommunication company using decision tree algorithm by Ramadhanti,, Darin, Larasati, Aisyah, Muid, Abdul, Mohamad, Effendi

“…Preventive efforts are needed by predicting the value of churn in the future. This study uses data mining techniques with decision tree algorithms to predict customer churn in one of Indonesian Telecommunication companies. …”
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Extended spatial decision tree algorithm for classifying hotspot occurrence by Sitanggang, Imas Sukaesih

“…This work proposes a new spatial decision tree algorithm namely the extended spatial ID3 decision tree algorithm to classify hotspots occurrence from a forest fires dataset that contains point, line and polygon features. …”
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Modeling forest fires risk using spatial decision tree by Yaakob, Razali, Mustapha, Norwati, Nuruddin, Ahmad Ainuddin, Sitanggang, Imas Sukaesih

“…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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Decision tree and rule-based classification for predicting online purchase behavior in Malaysia / Maslina Abdul Aziz, Nurul Ain Mustakim and Shuzlina Abdul Rahman by Abdul Aziz, Maslina, Mustakim, Nurul Ain, Abdul Rahman, Shuzlina

“…The study looks into the data from an online survey comprising 560 respondents with a view to demographic, factors influences, and purchasing behaviour. The performance of six machine learning models comprising J48, Random Tree, REPTree representing decision trees and JRip, PART, and OneR as rule-based algorithms was assessed. …”
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Predication of entropy generation rate in a concentrating photovoltaic thermal system with twisted tube turbulator using Boosted regression tree algorithm by Wang G., Paw J.K.S., Pasupuleti J., Yaw C.T., Yusaf T., Abdalla A.N., Cai Y.

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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Tree-based machine learning in classifying reverse migration/ Azreen Anuar, Nur Huzeima Mohd Hussain and Hugh Byrd by Anuar, Azreen, Mohd Hussain, Nur Huzeima, Byrd, Hugh

“…The study compares the performance of three types of treebased machine learning (Decision Tree, Random Forest, Gradient Boosted Trees) with linear-based algorithms (Logistic Regression, Fast Last Margin, Generalized Linear Model). …”
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Predicting Student Performance in Object Oriented Programming Using Decision Tree : A Case at Kolej Poly-Tech Mara, Kuantan by Mohd Hanis, Rani, Abdullah, Embong

“…The objective was to identify and implement the most accurate algorithm for the KPTM dataset and to come up with a good prediction model using decision tree technique. …”
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Reverse migration prediction model based on machine learning / Azreen Anuar by Anuar, Azreen

“…And the third objective is to evaluate reverse migration prediction model based on machine learning analysis. For this purpose, three (3) algorithms have been assessed, namely, the Random Forest, Decision Tree, and Gradient Boosted Tree. …”
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Classification model for hotspot occurrences using a decision tree method by Sitanggang, Imas Sukaesih, Ismail, Mohd Hasmadi

“…This work demonstrates the application of a decision tree algorithm, namely the C4.5 algorithm, to develop a classification model from forest fire data in the Rokan Hilir district, Indonesia. …”
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Prediction of life expectancy for Asian population using machine learning ALGORITHMS / Nurul Shahira Pisal, Shuzlina Abdul-Rahman, Mastura Hanafiah and Saidatul Izyanie Kamarudin by Pisal, Nurul Shahira, Abdul Rahman, Shuzlina, Hanafiah, Mastura, Kamarudin, Saidatul Izyanie

“…Comparisons are made between tree classifier models, namely, J48, Random Tree, and Random Forest. …”
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Predicting Customer Behaviour on Buying Life Insurance using Machine Learning by Fabu Ayub A Ghafar, Norhana Abd Rahim, Yumn Suhaylah Yusoff

Footwear quality evaluation using decision tree and logistic regression models by Tan, Swee Choon

“…The objectives of the study are to determine the rank factors that affect the quality of footwear using decision tree methods. …”
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Sales prediction of religious product and services of Mutawwif Haramain Travel & Tours using predictive analytics by Mohd Sabri, Nurul Ainin Qistina

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Machine learning versus linear regression modelling approach for accurate ozone concentrations prediction by Jumin E., Zaini N., Ahmed A.N., Abdullah S., Ismail M., Sherif M., Sefelnasr A., El-Shafie A.

“…Different Machine Learning algorithms have been investigated, viz. Linear Regression, Neural Network and Boosted Decision Tree. …”

A comparison of decision tree, logistic regression, artificial neural network and random forest algorithms to predict suicidal ideation among young adults in Malaysia by Chan, Sin Yin, Ch’ng, Chee Keong

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Not seeing the forest for the trees: Generalised linear model out-performs random forest in species distribution modelling for Southeast Asian felids by Chiaverini, Luca, Macdonald, David W., Hearn, Andrew J., Kaszta, Zaneta, Ash, Eric, Bothwell, Helen M., Can, Ozgun Emre, Channa, Phan, Clements, Gopalasamy Reuben *, Haidir, Iding Achmad, Kyaw, Pyae Phyoe, Moore, Jonathan H., Rasphone, Akchousanh, Tan, Cedric Kai Wei, Cushman, Samuel A.

“…Two of the most frequently applied algorithms to model species-habitat relationships are Generalised Linear Models (GLM) and Random Forest (RF). …”
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Differential Search Optimized Random Forest Regression Algorithm for State of Charge Estimation in Electric Vehicle Batteries by Hossain Lipu M.S., Hannan M.A., Hussain A., Ansari S., Ayob A., Saad M.H.M., Muttaqi K.M.