Search Results - (( using optimization learning algorithm ) OR ( data relation tree algorithm ))

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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Application of Decision Trees in Athlete Selection: A Cart Algorithm Approach by Riska Wahyu, Romadhonia, A'yunin, Sofro, Danang, Ariyanto, Dimas Avian, Maulana, Junaidi Budi, Prihanto

“…The focus of this study is on the use of DTs, employing the Classification and Regression Trees (CART) algorithm, in the initial screening of athletes. …”
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Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

“…The experimental results show that predictive FDT algorithm can generate a relatively optimal tree without much computation effort (comprehensibility), and WFPRs have a better predictive accuracy of stock market time series data. …”
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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

“…The Decision Tree algorithm was selected for its highest accuracy of 89.29%, reflecting its ability to accurately classify sales outcomes compared to the other models. …”
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Applications of Data-driven Models for Daily Discharge Estimation Based on Different Input Combinations by Kumar M., Elbeltagi A., Pande C.B., Ahmed A.N., Chow M.F., Pham Q.B., Kumari A., Kumar D.

Fraud detection in shipping industry based on location using machine learning comparison techniques by Ganesan Subramaniam, Mr.

“…A number of popular existing algorithms were used to execute the model developed in Rapid tool such as Naïve Bayes , Neural Net , Deep Learning, Decision Tree, Logistic Regression, SVM and k-NN. …”

Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach by Mustakim, Nurul Ain

“…The descriptive analysis examines purchasing behavior through correlation and regression analyses, while the predictive model uses decision trees (J48, Random Tree, REPTree), rule-based algorithms (JRip, OneR, PART), and clustering (K-Means) to identify patterns and predict trends. …”
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Solubility enhancement of decitabine as anticancer drug via green chemistry solvent: Novel computational prediction and optimization by Nader Ibrahim Namazi, Sameer Alshehri, Rawan Bafail, Bader Huwaimel, Amal M. Alsubaiyel, Ali H. Alamri, Ahmed D. Alatawi, Hossam Kotb, Mohd Sani Sarjadi, Md. Lutfor Rahman, Mohammed A.S. Abourehab

“…One of the two input features is P (bar) and the other is T (k). ADA-DT (Adaboost Algorithm Decision Tree), ADA-LR (Adaboost Algorithm-Linear Regresion), and ADA-GRNN (Generative Regression Neural Network) models showed MAE of 6.54 ˣ 10ˉ⁵, 4.66 10 ˉ⁵, and 8.35 10 ˉ⁵, respectively. …”
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Analysis of daytime and nighttime ground level ozone concentrations using boosted regression tree technique by Yahaya, Noor Zaitun, Ghazali, Nurul Adyani, Ahmad, Sabri, Mohammad Asri, Mohammad Akmal, Ibrahim, Zul Fahdli, Ramli, Nor Azman

“…The ozone BRT algorithm model was constructed from multiple regression models, and the ‘best iteration’ of BRT model was performed by optimizing prediction performance. …”
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State-of-charge estimation for lithium-ion batteries with optimized self-supervised transformer deep learning model by Dickson Neoh Tze How, Dr.

“…In the first stage, the model is pre-trained using unlabeled data with unsupervised learning. …”

Artificial intelligence system for pineapple variety classification and its quality evaluation during storage using infrared thermal imaging by Mohd Ali, Maimunah

“…Several machine learning algorithms including linear discriminant analysis, quadratic discriminant analysis, k-nearest neighbour, support vector machine, decision tree, and Naïve Bayes were applied for the classification of pineapple varieties. …”
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Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems by Din, Fakhrud, Khalid, Shah, Fayaz, Muhammad, Gwak, Jeonghwan, Kamal Z., Zamli, Mashwani, Wali Khan

“…Teaching learning-based optimization is one of the widely accepted metaheuristic algorithms inspired by teaching and learning within classrooms. …”
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An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM) by Shamim, Akhtar

“…Therefore, in this study a new optimized variant of machine learning algorithms is presented. …”
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An Efficient Data Structure for General Tree-Like Framework in Mining Sequential Patterns Using MEMISP by Saputra, Dhany, Rambli, Dayang R.A., Foong, Oi Mean

“…Sequential pattern mining is a relatively new data-mining problem with many areas of applications. …”
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An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction by Shah, Habib

“…Backpropagation (BP) learning algorithm is the well-known learning technique that trained ANN. …”
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Combining object-based classification and data mining algorithm to classify urban surface materials from worldview-2 satellite image by Hamedianfar, Alireza, Mohd Shafri, Helmi Zulhaidi

“…This algorithm provides a decision tree output to represent the knowledge model, enabled a faster classification of intra-urban classes, and disabled the subjectivities which are related to the interaction of the analyst. …”
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Particle swarm optimization for neural network learning enhancement by Abdull Hamed, Haza Nuzly

“…To overcome this problem, Genetic Algorithm (GA) has been used to determine optimal value for BP parameters such as learning rate and momentum rate and also for weight optimization. …”
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Predicting longitudinal dispersion coefficient using ensemble models and optimized multi-layer perceptron models by Gholami M., Ghanbari-Adivi E., Ehteram M., Singh V.P., Najah Ahmed A., Mosavi A., El-Shafie A.

Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Nor Farizan, Zakaria, Mohd Mawardi, Saari

“…This paper presents the application of a recent metaheuristic algorithm namely Evolutionary Mating Algorithm (EMA) for optimizing the Deep Learning (DL) parameters to estimate the state of charge (SOC) of a battery for an electric vehicle in the real environment. …”
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Optimization of cost-based hybrid flowshop scheduling using teaching-learning-based optimization algorithm by Ullah, Wasif, Muhammad Ammar, Nik Mu’tasim, Mohd Fadzil Faisae, Ab Rashid

“…This paper investigates the optimization of a CHFS problem using the Teaching Learning-Based Optimization (TLBO) algorithm. …”
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