Search Results - (( developing boosts selection algorithm ) OR ( java application mining algorithm ))

Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

Get full text
Get full text

Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

Get full text
Get full text

Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
Get full text
Get full text
Get full text

Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

“…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
Get full text
Get full text
Get full text

A web-based implementation of k-means algorithms by Lee, Quan

“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
Get full text
Get full text

Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

Get full text
Get full text

Gene Selection For Cancer Classification Based On Xgboost Classifier by Teo, Voon Chuan

“…Gene selection is the technique that applied to the gene selection dataset, such as DNA microarray, which is develop to reduce the less informative gene, so that the selected gene is related to the disease diagnosis. …”
Get full text
Get full text

Streamflow Prediction Utilizing Deep Learning and Machine Learning Algorithms for Sustainable Water Supply Management by Latif S.D., Ahmed A.N.

Extreme Gradient Boosting (XGBoost) and Random Forest (RF) Hybrid Ensemble with Bayesian Optimization in Landslide Susceptibility Mapping by Dorothy, Anak Martin Atok

“…Many models have been developed in the past for predicting landslide vulnerability. …”
Get full text
Get full text
Get full text
Get full text

Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
Get full text
Get full text

Prediction of employee promotion using hybrid sampling method with machine learning architecture / Shahidan Shafie, Soek Peng Ooi and Khai Wah Khaw by Shafie, Shahidan, Soek, Peng Ooi, Khai, Wah Khaw

“…The first 5, 8, and 12 features are selected based on the RFI-ECT to train the machine learning algorithms. …”
Get full text
Get full text
Get full text

Machine learning-based risk prediction model for medication administration errors in neonatal intensive care units: a prospective direct observational study by Henry Basil, Josephine, Lim, Wern Han, Syed Ahmad, Sharifah M., Menon Premakumar, Chandini, Mohd Tahir, Nurul Ain, Mhd Ali, Adliah, Seman, Zamtira, Ishak, Shareena, Mohamed Shah, Noraida

“…AdaBoost was identified as the best-performing algorithm. …”
Get full text
Get full text
Get full text

BCLH2Pro: a novel computational tools approach for hydrogen production prediction via machine learning in biomass chemical looping processes by Tuntiwongwat, Thanadol, Thammawiset, Sippawit, Srinophakun, Thongchai Rohitatisha, Ngamcharussrivichai, Chawalit, Sukpancharoen, Somboon

“…The algorithm has been developed into a user-friendly tool, BCLH2Pro, accessible via a web server. …”
Get full text
Get full text
Get full text

A high-performance control scheme for photovoltaic pumping system under sudden irradiance and load changes by Talbi, Billel, Krim, Fateh, Rekioua, Toufik, Mekhilef, Saad, Laib, Abdelbaset, Belaout, Abdesslam

“…The proposed algorithm is based on a current control approach of the boost converter with a model predictive current controller to select the optimal control action. …”
Get full text
Get full text

Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

“…The proposed algorithm is compared with the state-of-the-art feature selection algorithms using three different datasets. …”
Get full text
Get full text
Get full text

Prediction of Oil Palm Yield Using Machine Learning in the Perspective of Fluctuating Weather and Soil Moisture Conditions: Evaluation of a Generic Workflow by Khan N., Kamaruddin M.A., Ullah Sheikh U., Zawawi M.H., Yusup Y., Bakht M.P., Mohamed Noor N.

“…The prediction was followed by data preprocessing and feature selection. Selected regression models were compared with Random Forest, Gradient Boosting, Decision Tree, and other non-tree algorithms to prove the R2 driven performance superiority of tree-based ensemble models. …”

Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

“…This study utilizes genetic algorithms based upon the medoid rather than the mean as a centroid-selection schema to improve the clustering efficiency. …”
Get full text
Get full text

Water Quality Parameter Prediction Using Machine Learning Method by Muhammad Shaiful Bin Abdul Halim

Utilizing machine learning to predict hospital admissions for pediatric COVID-19 patients (PrepCOVID-Machine) by Chuin-Hen Liew, Song-Quan Ong, David Chun-Ern Ng

“…The RFE algorithm selected 12 highly predicted variables for COVID-19 hospitalization, including age, male sex, fever, cough, rhinorrhea, shortness of breath, vomiting, diarrhea, seizures, body temperature, chest indrawing, and abnormal breath sounds. …”
Get full text
Get full text
Get full text

A Simplified Time-Domain Modulation Scheme-Based Maximum Boost Control for Three-Phase Quasi-Z Source Inverters by Sabeur, Nassereddine, Mekhilef, Saad, Masaoud, Ammar

Get full text
Get full text