Search Results - (( _ evaluation between algorithm ) OR ( data classification modeling algorithm ))*

Classification for large number of variables with two imbalanced groups by Ahmad Hakiim, Jamaluddin

“…This study proposed two algorithms of classification namely Algorithm 1 and Algorithm 2 which combine resampling, variable extraction, and classification procedure. …”
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A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification by Talpur, N., Abdulkadir, S.J., Hasan, M.H., Alhussian, H., Alwadain, A.

“…Moreover, K-Nearest Neighbor (KNN) classifier was used to evaluate the effectiveness of the features identified by the proposed SCSO algorithm. …”
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Sentiment analysis of hotel reviews using Convolutional Neural Network / Sofea Aini Mohd Sufian by Mohd Sufian, Sofea Aini

“…So, the aim of this paper is to develop a prototype for hotel reviews using CNN Algorithm, to identify the requirements of CNN technique for text classification and also to evaluate the accuracy of CNN algorithm. …”
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Predicting building damage grade by earthquake: a Bayesian Optimization-based comparative study of machine learning algorithms by Al-Rawashdeh, Mohammad, Al Nawaiseh, Moh’d, Yousef, Isam, Bisharah, Majdi, Alkhadrawi, Sajeda, Al-Bdour, Hamza

“…This study compares Bayesian Optimization-based machine learning systems that anticipate earthquake-damaged buildings and to evaluates building damage classification models. Using metrics, this study evaluates Random Forest, ElasticNet, and Decision Tree algorithms. …”
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Improved cuckoo search based neural network learning algorithms for data classification by Abdullah, Abdullah

“…It can also be used to improve the balance between exploration and exploitation of CS algorithm, and to increase the chances of the egg’s survival. …”
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A novelty classification model for varied agarwood oil quality using the K-Nearest Neighbor algorithm / Aqib Fawwaz Mohd Amidon … [et al.] by Mohd Amidon, Aqib Fawwaz, Mohd Huzir, Siti Mariatul Hazwa, Mohd Yusoff, Zakiah, Ismail, Nurlaila, Taib, Mohd Nasir

“…As a result, a new grading system based on artificial algorithms, namely K-Nearest Neighbor algorithms, was established. …”
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Classification of cervical cancer using random forest by Bahirah, Mohd Bashah, Ku Muhammad Naim, Ku Khalif, Nor Azuana, Ramli

“…Model evaluation has been conducted to identify the robust data mining algorithm in the prediction of cervical cancer risk. …”
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Water Quality Evaluation and Analysis by Integrating Statistical and Machine Learning Approaches by Amar Lokman, Wan Zakiah Wan Ismail, Nor Azlina Ab Aziz

Multi-label risk diabetes complication prediction model using deep neural network with multi-channel weighted dropout by Dzakiyullah, Nur Rachman

“…The proposed method managed data and model complexity effectively while maintaining high computational efficiency. …”
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An automatic grading model for semantic complexity of english texts using bidirectional attention-based autoencoder by Chen, Ruo Han, Ng, Boon Sim, Paramasivam, Shamala, Ren, Li

“…The experimental results show that the overall accuracy of BSETG algorithm is maintained between 70% and 90%, the response speed of BSETG algorithm is relatively fast, and the success rate of BSETG algorithm is relatively stable to a large extent.…”
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The formulation of a transfer learning pipeline for the classification of the wafer defects by Lim, Shi Xuen

“…It is observed that the ResNet101v2 model pairing up with an optimized SVM pipeline is able to achieve the best classification accuracy of 95% for training, validation and testing data.…”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…Then, this study aims to optimize the hyperparameters of the developed DNN model using the Arithmetic Optimization Algorithm (AOA) and, lastly, to evaluate the performance of the newly proposed deep learning model with Simulated Kalman Filter (SKF) algorithm in solving image encryption application. …”
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Evaluating Adan vs. Adam: an analysis of optimizer performance in deep learning by Ismail, Amelia Ritahani, Azhary, Muhammad Zulhazmi Rafiqi, Hitam, Nor Azizah

“…Choosing a suitable optimization algorithm in deep learning is essential for effective model development as it significantly influences convergence speed, model performance, and the success of the train- ing process. …”
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Detection of leak size and its location in a water distribution system by using K-NN / Nasereddin Ibrahim Sherksi by Sherksi, Nasereddin Ibrahim

“…The successfully achieved four set objectives inclusive of (1) a new classification model to detect water leakage, (2) analysis of the effects of leakage size on the variables within a WDS, i.e. flow, pressure, pipe volume, velocity and water demand, (3) locating and specifying the leakage size in the WDS, and (4) evaluate the performance of the designed K-NN algorithm for accurate leak detection. …”
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The classification of wink-based eeg signals by means of transfer learning models by Jothi Letchumy, Mahendra Kumar

“…Whilst it was observed that the optimized k-NN model based on the aforesaid pipeline could achieve a classification accuracy of 100% for the training, validation, and tes t data. …”
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An improved plant identification system by Fuzzy c-means bag of visual words model and sparse coding by Safa, Soodabeh, Khalid, Fatimah

“…In the classic Bag of visual words model, the Fuzzy c-means algorithm is replaced with K-means and the accuracy of SIFT matching is increased. …”
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Software defect prediction framework based on hybrid metaheuristic optimization methods by Wahono, Romi Satria

“…For the purpose of this study, ten classification algorithms have been selected. The selection aims at achieving a balance between established classification algorithms used in software defect prediction. …”
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On the training sample size and classification performance: An experimental evaluation in seismic facies classification by Babikir, I., Elsaadany, M., Sajid, M., Laudon, C.

“…Machine learning algorithms (MLAs) perform better when enough high-quality training data is provided. …”
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Convolutional neural network based mobile application for poisonous mushroom detection by Amirul, Shazlin Nizam, Mohd Sabri, Norlina, Gloria, Jennis Tan, Redwan, Nurul Ainina, Zhiping, Zhang

“…There are 3 main phases of the research methodology, which cover the data collection and preprocessing, model design and implementation, and performance evaluation. …”
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Deep learning-based colorectal cancer classification using augmented and normalised gut microbiome data / Mwenge Mulenga by Mwenge , Mulenga

“…Considering the limitations of existing methods for colorectal cancer detection, such as colonoscopy and faecal occult blood test, the medical research community has adopted the use of sequence data to identify the disease. While the complex relations that exist between the microbiome and host phenotypes make machine learning algorithms suitable for analysing the microbiome data, deep learning methods are becoming more popular due to their outstanding performance in related fields. …”
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