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  1. 1
    Attribute related methods for improvement of ID3 Algorithm in classification of data: A review

    Attribute related methods for improvement of ID3 Algorithm in classification of data: A review by Nur Farahaina, Idris, Mohd Arfian, Ismail

    Published 2020
    “…Decision tree is an important method in data mining to solve the classification problems. …”
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  2. 2
    Modeling forest fires risk using spatial decision tree

    Modeling forest fires risk using spatial decision tree by Yaakob, Razali, Mustapha, Norwati, Nuruddin, Ahmad Ainuddin, Sitanggang, Imas Sukaesih

    Published 2011
    “…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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  3. 3
    Application of Decision Trees in Athlete Selection: A Cart Algorithm Approach

    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

    Published 2023
    “…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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  4. 4
    An efficient indexing and retrieval of iris biometrics data using hybrid transform and firefly based K-means algorithm title

    An efficient indexing and retrieval of iris biometrics data using hybrid transform and firefly based K-means algorithm title by Khalaf, Emad Taha

    Published 2019
    “…To overcome this disadvantage, the Fireflies Algorithm (FA) was used because it has the ability to perform global searches and has quick convergence rate to optimize the initial clustering centers of the K-means algorithm, using a kind of weighted Euclidean distance to reduce the defects made by noise data and other uncertainties. …”
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  5. 5
    Classification with degree of importance of attributes for stock market data mining

    Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

    Published 2004
    “…The predictive FDT has been tested using three data sets including KLSE, NYSE and LSE. 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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  6. 6
    A matrix approach for minimum spanning tree in neutrosophic and application in medical waste management / Nur Haifa Ahmad Hayazim, Siti Nurain Zulkifli and Siti Nurhidayah Yaacob

    A matrix approach for minimum spanning tree in neutrosophic and application in medical waste management / Nur Haifa Ahmad Hayazim, Siti Nurain Zulkifli and Siti Nurhidayah Yaacob by Ahmad Hayazim, Nur Haifa, Zulkifli, Siti Nurain, Yaacob, Siti Nurhidayah

    Published 2022
    “…As a final step, a comparative study such as interval-valued neutrosophic minimum spanning tree (IVN-MST), interval-valued intuitionistic fuzzy minimum spanning tree (IVIF-MST) and interval-valued fuzzy minimum spanning tree (IVE-MST) is presented to point out the advantages of the proposed method over that of other existing algorithms. …”
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  7. 7
    Applications of Data-driven Models for Daily Discharge Estimation Based on Different Input Combinations

    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.

    Published 2023
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  8. 8
    Solubility enhancement of decitabine as anticancer drug via green chemistry solvent: Novel computational prediction and optimization

    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

    Published 2022
    “…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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  9. 9
    Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach

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

    Published 2025
    “…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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  10. 10
    State-of-charge estimation for lithium-ion batteries with optimized self-supervised transformer deep learning model

    State-of-charge estimation for lithium-ion batteries with optimized self-supervised transformer deep learning model by Dickson Neoh Tze How, Dr.

    Published 2023
    “…The Transformer model with transferred weights outperformed models trained from scratch using supervised learning. To select the optimal hyperparameters for the Transformer model, the Tree Parzen Estimator(TPE) optimization in combination with the Hyperband pruning algorithm is employed to search for the best combination that yields the lowest Root Mean Squared Error(RMSE)and Mean Absolute Error (MAE) error metrics. …”
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  11. 11
    An extreme gradient boosting for cancer feature extraction and classification

    An extreme gradient boosting for cancer feature extraction and classification by Chuan, Teo Voon, Moorthy, Kohbalan, Nasarudin, Ismail, Mohd. Murtadha, Mohamad, Howe, Chan Weng

    Published 2025
    “…This research focuses on improving gene selection for cancer classification using the XGBoost classifier, an efficient open-source implementation of the gradient-boosted trees algorithm. The primary goal is to enhance the performance of gene selection, enabling timely and appropriate treatments for cancer patients, as early detection is vital for ensuring a full recovery. …”
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  12. 12
    Gene Selection for Cancer Classification Based on XGBoost

    Gene Selection for Cancer Classification Based on XGBoost by Chuan, Teo Voon, Tomal, Md Raihanul Islam, Moorthy, Kohbalan, Howe, Chan Weng

    Published 2025
    “…This research focuses on improving gene selection for cancer classification using the XGBoost classifier, an efficient open-source implementation of the gradient boosted trees algorithm. The primary goal is to enhance the performance of gene selection, enabling timely and appropriate treatments for cancer patients, as early detection is vital for ensuring a full recovery. …”
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  13. 13
    An Efficient Data Structure for General Tree-Like Framework in Mining Sequential Patterns Using MEMISP

    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

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of applications. …”
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  14. 14
    Combining object-based classification and data mining algorithm to classify urban surface materials from worldview-2 satellite image

    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

    Published 2014
    “…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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  15. 15
    Case Slicing Technique for Feature Selection

    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    Published 2004
    “…Since the 1960s, many algorithms for data classification have been proposed. …”
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  16. 16
    Cancer Prediction Based On Data Mining Using Decision Tree Algorithm

    Cancer Prediction Based On Data Mining Using Decision Tree Algorithm by Loh, Kin Ming

    Published 2022
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  17. 17
    VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern

    VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern by Angeline Teoh, Szu Fern

    Published 2012
    “…These two models are based on topological placement method. DM is optimized using genetic algorithm (GA). …”
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  18. 18
    Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm

    Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm by Islam, Muhammad Shafiqul, Mohd Ashraf, Ahmad

    Published 2024
    “…This research introduces the improved Archimedes optimization algorithm (IAOA) for data-driven modeling of continuous-time Hammerstein models with missing data. …”
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  19. 19
    Predicting future sales using genetic algorithm: data mining sales / Siti Hajar Yaacob

    Predicting future sales using genetic algorithm: data mining sales / Siti Hajar Yaacob by Yaacob, Siti Hajar

    Published 2014
    “…Besides that, Genetic Algorithm is applying to predict future sales based on the sales and product data. …”
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  20. 20
    A study of graduate on time (GOT) for Ph.D students using decision tree model

    A study of graduate on time (GOT) for Ph.D students using decision tree model by Chin, Wan Yung, Ch’ng, Chee Keong, Mohd Jamil, Jastini

    Published 2019
    “…Therefore, this study aims to classify the Ph.D students into the group of “GOT achiever” and “non-GOT achiever” by using decision tree models. Historical data that related to all Ph.D students in a public university in Malaysia has been obtained directly from the database of Graduate Academic Information System (GAIS) in order to develop and compare the performance of decision tree models (Chi-square algorithm, Gini index algorithm, Entropy algorithm and an interactive decision tree). …”
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