Search Results - (( java application customization algorithm ) OR ( missing value based 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.

“…This problem inspires the idea to develop a prediction algorithm to predict the missing values in the dataset, where Support vector regression (SVR) has been proposed as a prediction method to predict missing values in several academic types of researches. …”
Get full text
Get full text

An Evaluation of Machine Learning Algorithms for Missing Values Imputation by Kohbalan, Moorthy, Ali, Mohammed Hasan, Mohd Arfian, Ismail, Chan, Weng Howe, Mohd Saberi, Mohamad, Safaai, Deris

“…Hence, it is necessary to resolve this problem of missing values imputation. Our research paper presents a review of missing values imputation approaches. …”
Get full text
Get full text
Get full text

Missing-values imputation algorithms for microarray gene expression data by Moorthy, Kohbalan, Jaber, Aws Naser, Mohd Arfian, Ismail, Ernawan, Ferda, Mohd Saberi, Mohamad, Safaai, Deris

“…By using local and global correlation of the data, we were able to focus mostly on the differences between the algorithms. We classified the algorithms as global, hybrid, local, or knowledge-based techniques. …”
Get full text
Get full text
Get full text
Get full text
Get full text
Get full text

An improved K-nearest neighbour with grasshopper optimization algorithm for imputation of missing data by Zainal Abidin, Nadzurah, Ismail, Amelia Ritahani

“…K-nearest neighbors (KNN) has been extensively used as imputation algorithm to substitute missing data with plausible values. …”
Get full text
Get full text
Get full text

New Learning Models for Generating Classification Rules Based on Rough Set Approach by Al Shalabi, Luai Abdel Lateef

“…Missing values in that attribute were replaced by the mode value. …”
Get full text
Get full text

Missing Value Imputation for PM10 Concentration in Sabah using Nearest Neighbour Method(NNM) and Expectation-Maximization (EM) Algorithm by Muhammad Izzuddin Rumaling, Chee, Fuei Pien, Jedol Dayou, Chang, Jackson Hian Wui, Steven Soon Kai Kong, Justin Sentian

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

SINE COSINE ALGORITHM BASED NEURAL NETWORK FOR RAINFALL DATA IMPUTATION by Chiu, Po Chan, Ali, Selamat, Kuok, King Kuok

“…This chapter presents the ability of the sine cosine algorithm-based neural network (SCANN) to predict and optimize missing rainfall at different percentages of missing rates. …”
Get full text
Get full text
Get full text

Detection Of Misplaced And Missing Regions In Image Using Neural Network by Tan , Jin Siang

“…Therefore, it is necessary to develop an algorithm that is able to detect both misplaced and missing jigsaw puzzles. …”
Get full text
Get full text

Restoration of missing data in old archives based on genetic algorithm by Khammar, Mohammad Reza, Saripan, M. Iqbal, Marhaban, Mohammad Hamiruce, Ishak, Asnor Juraiza, Zolfaghari, Fateme

Get full text
Get full text

Confidence intervals (CI) for concentration parameter in von Mises distribution and analysis of missing values for circular data / Siti Fatimah binti Hassan by Hassan, Siti Fatimah

“…The final part of this study is an analysis of missing values for circular variables. Missing values is a common problem that occurs in data collection. …”
Get full text
Get full text

Missing values imputation tool using imputex algorithm by Sidi, Fatimah, Abdullah, Lili Nurliyana, Alabadla, Mustafa, Ishak, Iskandar

Get full text
Get full text
Get full text

Evaluating A New Adaptive Group Lasso Imputation Technique For Handling Missing Values In Compositional Data by Tian, Ying

“…The complexity of compositional data with missing values renders traditional estimation methods inadequate. …”
Get full text
Get full text

Survival modelling, missing values and frailty with application to cervical cancer data / Nuradhiathy Abd Razak by Nuradhiathy, Abd Razak

“…The values are assumed missing at random (MAR). Simulation studies are performed, and the cervical cancer data is used for illustration. …”
Get full text
Get full text

Missing value estimation methods for data in linear functional relationship model by Adilah Abdul Ghapor, Yong Zulina Zubairi, A.H.M. Rahmatullah Imon

“…Missing value problem is common when analysing quantitative data. …”
Get full text
Get full text
Get full text

A Rough Set-Based Approach for Identifying and Replacing Missing Concepts in Incomplete Sentences in Computer Domain Texts by Nur Faiqah ‘Aqilah binti Fuaad

An Apriori-based Data Analysis on Suspicious Network Event Recognition by Jian, Z., Sakai, H., Watada, J., Roy, A., Hassan, M.H.B.

“…Then, each missing value in the test data set is decided by using the obtained rules. …”
Get full text
Get full text

A novel approach for handling missing data to enhance network intrusion detection system by Tahir, Mahjabeen, Abdullah, Azizol, Udzir, Nur Izura, Kasmiran, Khairul Azhar

“…Our approach employs the Random Missing Value (RMV) algorithm to simulate missing data, enabling thorough testing and comparison of various imputation techniques. …”
Get full text
Get full text
Get full text

Interpolation and Extrapolation Techniques Based Neural Network in Estimating the Missing Ionospheric TEC Data by Jayapal, V, Zain, AFM

Interpolation and extrapolation techniques based Neural Network in estimating the missing ionospheric TEC data by Jayapal V., Zain A.F.M.

“…The NN2 model finds hard to extrapolate the missing TEC data especially during the night hours, where the GPS TEC values are underestimated. …”

Development of an imputation technique - INI for software metric database with incomplete data by Wasito, Ito, Olanrewaju, Rashidah F.

“…In this paper, an imputation technique for imputing missing data based on global-local Modified Singular Value Decomposition (MSVD) algorithm, INI was proposed. …”
Get full text
Get full text
Get full text