Search Results - (( java implementation force algorithm ) OR ( missing make learning algorithm ))

Auto-feed hyperparameter support vector regression prediction algorithm in handling missing values in oil and gas dataset by Amirruddin, A., Aziz, I.A., Hasan, M.H.

“…Missing values in datasets is a synonymous problem in data mining which could lead to an incomplete dataset, making inaccurate predictions results in machine learning prediction processes. …”
Get full text
Get full text

ExtraImpute: a novel machine learning method for missing data imputation by Alabadla, Mustafa, Sidi, Fatimah, Ishak, Iskandar, Ibrahim, Hamidah, Affendey, Lilly Suriani, Hamdan, Hazlina

“…In this paper, we propose a new imputation approach using Extremely Randomized Trees (Extra Trees) of machine learning ensemble learning methods named (ExtraImpute) to tackle numerical missing values in healthcare context. …”
Get full text
Get full text

An improved machine learning model of massive Floating Car Data (FCD) based on Fuzzy-MDL and LSTM-C for traffic speed estimation and prediction by Ahanin, Fatemeh

Get full text
Get full text
Get full text

Enhanced Distributed Learning Classifier System For Simulated Mobile Robot Behaviours by Baneamoon, Saeed Mohammed Saeed

“…Overall, the enhanced approaches performed well and the enhanced learning processes proposed in the current study makes robot learning more effective. …”
Get full text
Get full text

Kelantan daily water level prediction model using hybrid deep-learning algorithm for flood forecasting by Loh, Eng Chuen

“…Next, a newly developed hybrid deep learning (DL) algorithm is proposed to predict the daily water level in selected rivers that flow through Kelantan. …”
Get full text
Get full text
Get full text
Get full text

A systematic review of recurrent neural network adoption in missing data imputation by Nur Aqilah, Fadzil Akbar, Mohd Izham, Mohd Jaya, Mohd Faizal, Ab Razak, Nurul Aqilah, Zamri

“…Missing data is a pervasive challenge in diverse datasets accross various domains. …”
Get full text
Get full text
Get full text

Development of intelligent hybrid learning system using clustering and knowledge-based neural networks for economic forecasting : First phase by Che Mat @ Mohd Shukor, Zamzarina, Md Sap, Mohd Noor

“…We proposed KMeans clustering algorithm that is based on multidimensional scaling, joined with neural knowledge based technique algorithm for supporting the learning module to generate interesting clusters that will generate interesting rules for extracting knowledge from stock exchange databases efficiently and accurately.…”
Get full text
Get full text
Get full text

Predicting Breast Cancer Intelligently with Machine Learning Techniques by Manimozhi, I., Laksmi, D.

“…Feature selection methods are employed to extract the most relevant attributes influencing prediction performance. Multiple machine learning algorithms, such as Support Vector Machine (SVM), Random Forest, Naïve Bayes, Logistic Regression, and K-Nearest Neighbors (KNN), are implemented and compared. …”
Get full text
Get full text
Get full text
Get full text

A review of knowledge graph embedding methods of TransE, TransH and TransR for missing links by Salwana, Mohamad, Noor Azida, Sahabudin, Nor Syahidatul Nadiah, Ismail, Ily Amalina, Ahmad Sabri

Get full text
Get full text
Get full text
Get full text

Sentiment analysis of customer review for Tina Arena Beauty by Amri, Nur Najwa Shahirah

“…Customer review data were collected from multiple platforms and processed using Natural Language Processing (NLP) techniques such as Term Frequency-Inverse Document Frequency (TF-IDF). Three machine learning algorithms Naive Bayes, Random Forest, and Support Vector Machine (SVM) were evaluated, and SVM achieved the highest accuracy and was selected as the final classifier. …”
Get full text
Get full text

Deep learning-based classification of breast tumors in ultrasound images / Ayub Ahmed Omar by Ayub Ahmed, Omar

Get full text
Get full text
Get full text

Predictive analytics for the sentiment of malaysian place of interest using machine learning models by Qiryn Adriana, Kharul Zaman

“…Furthermore, this study also trains three machine learning algorithms to predict the sentiment of textual data. …”
Get full text
Get full text

Early Detection of Breast Cancer with Microcalcifications on Mammography Using Deep Learning by Ibrahim, Ashraf Osman, Abuharaz, Hafia Mamoun Ismail, Saleh, Mohammed A, Alharith, Razan

“…This study's contribution is the innovative use of advanced deep learning algorithms to a major issue in medical imaging, which represents a significant improvement over current diagnostic approaches. © 2025 IEEE.…”
Get full text
Get full text

Reassembly and clustering bifragmented intertwined jpeg images using genetic algorithm and extreme learning machine by Raad Ali, Rabei

“…Today, JPEG image files are popular file formats that have less structured contents which make its carving possible in the absence of any file system metadata. …”
Get full text
Get full text
Get full text
Get full text

Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli by Ahmad Kamaruddin, Saadi, Md. Ghani, Nor Azura, Mohamed Ramli, Norazan

“…Most of the previous studies seek to improve the learning algorithm of backpropagation neural networks by adapting the M-estimators predominantly. …”
Get full text
Get full text
Get full text

Rain classification for autonomous vehicle navigation : A support vector machine approach by Abdul Haleem, Habeeb Mohamed, Muhammad Aizzat, Zakaria, Mohd Azraai, Mohd Razman, Anwar P. P., Abdul Majeed, Mohamad Heerwan, Peeie

“…Despite that, the ability of the sensor to adjust to human behaviour in sensing and perceiving different environments is still unsolved as it significantly impacting the performance of LIDAR, causing the effect of missing points and false positives detection. The immerging of machine learning algorithms that have greatly impacted solving uncertainties and LIDAR's reliability in making judgments has proven a great success. …”
Get full text
Get full text
Get full text

Risk-ranking matrix for security patching of exploitable vulnerabilities by Hoque M.S., Jamil N., Amin N., Mansor M.

“…The literature review shows that there are existing research works with machine learning approaches to forecast the number of future vulnerabilities and to predict the highly exploitable vulnerabilities, but the literature shows that a risk ranking matrix is missing in this domain. …”

Evaluation Of Renal Safety Of Raas Inhibitor Therapy: A Clinical And Pharmacovigilant Study by Khaleel, Mohammad Ali Mohammad

“…The predictive model would help physicians to easily highlight patients at high risk, make sure those patients will not miss the monitoring tests, and give physicians a chance to be proactive with patients’ treatment plans rather than reactive. …”
Get full text
Get full text

Incremental learning for large-scale stream data and its application to cybersecurity by Ali, Siti Hajar Aminah

“…To process large-scale data sequences, it is important to choose a suitable learning algorithm that is capable to learn in real time. …”
Get full text
Get full text

Abnormal event detection in video surveillance / Lim Mei Kuan by Lim, Mei Kuan

“…Therefore, by considering tracking as an optimisation problem, the proposed SwATrack algorithm searches for the optimal distribution of motion model without making prior assumptions, or prior learning of the motion model. …”
Get full text
Get full text