Search Results - (( data distribution mining algorithm ) OR ( re evaluation step algorithm ))

Satisfiable Integer Programming Algorithm On Distributed Inter Process Communication (SIP-DIPC) by Abdul Hamid, Mohd Hakim, Abu, Nur Azman, Mohamad, Siti Nurul Mahfuzah, Idris, Aris, Zakaria, Zahriladha, Sulaiman, Zuraidah

“…Data Analytics is a superset to Data Mining. Data mining algorithm is getting popular support in recent development of Big Data. …”
Get full text
Get full text
Get full text

Discovery of SIP/DRIP approach in distributed inter process communication by Hamid H., Jais J.

“…Classification modeling in data mining has evolved since 1990's. Many methods have been introduced and experimented. …”

Analysis using data mining techniques: the exploration and review data of diabetes patients / Syarifah Adilah Mohamed Yusoff ... [et al.] by Mohamed Yusoff, Syarifah Adilah, Othman, Jamal, Johan, Elly Johana, Mohd Mydin, Azlina, Wan Mohamad, Wan Anisha

“…In this statistical summary procedure, the distribution of attributes and their interactions are crucial for accurately processing the data in accordance with the selected classification or data mining techniques to be performed. …”
Get full text
Get full text
Get full text

A negotiation algorithm for decision-making in the construction domain by Idrus A., Mahmoud M.A., Ahmad M.S., Yahya A., Husen H.

Parallel execution of distributed SVM using MPI (CoDLib) by Salleh N.S.M., Suliman A., Ahmad A.R.

Subjects:

Effect of corrugated wall combined with backward-facing step channel on fluid flow and heat transfer by Hilo, Ali Kareem, Abu Talib, Abd Rahim, Iborra, Antonio Acosta, Hameed Sultan, Mohamed Thariq, Abdul Hamid, Mohd Faisal

“…Combining the corrugated wall with backward-facing step enhanced the Nusselt number (Nu) up to 62% at Re = 5000. …”
Get full text
Get full text
Get full text

Predicting Customer Buying Decisions for Online Shopping with Unbalanced Data Set by Yap, Chau Tean

“…Weka, a data mining tool, provides the facility to classify the data set with different machine learning algorithms. …”
Get full text
Get full text

Algorithm Development of Bidirectional Agglomerative Hierarchical Clustering Using AVL Tree with Visualization by Hussain Mohammad Yousef Abu Dalbouh

Unsupervised logic mining with a binary clonal selection algorithm in multi-unit discrete Hopfield neural networks via weighted systematic 2 satisfiability by Romli, Nurul Atiqah, Zulkepli, Nur Fariha Syaqina, Kasihmuddin, Mohd Shareduwan Mohd, Zamri, Nur Ezlin, Rusdi, Nur 'Afifah, Manoharam, Gaeithry, Mansor, Mohd. Asyraf, Jamaludin, Siti Zulaikha Mohd, Malik, Amierah Abdul

Get full text
Get full text
Get full text

Building classification models from imbalanced fraud detection data / Terence Yong Koon Beh, Swee Chuan Tan and Hwee Theng Yeo by Terence, Yong Koon Beh, Swee, Chuan Tan, Hwee, Theng Yeo

“…Building classification models from such imbalanced data sets is a relatively new challenge in the machine learning and data mining community because many traditional classification algorithms assume similar proportions of majority and minority classes. …”
Get full text
Get full text
Get full text

Binary vote assignment on grid quorum replication technique with association rule by Ainul Azila, Che Fauzi

“…Performance of the BVAGQ-AR technique comprised the following steps. First step is mining the data by using Apriori algorithm from Association Rules. …”
Get full text
Get full text

A novel approach to data mining using simplified swarm optimization by Wahid, Noorhaniza

“…Data mining has become an increasingly important approach to deal with the rapid growth of data collected and stored in databases. …”
Get full text
Get full text

Nanofluid flow and heat transfer in corrugated backward-facing step channel using ethylene glycol as based fluid by Hilo, Al Behadili Ali Kareem

“…Combined the backward-facing step with corrugated wall enhanced the Nusselt number (Nu) up to 62% at Re = 5,000. …”
Get full text
Get full text

Logistic regression methods for classification of imbalanced data sets by Santi Puteri Rahayu, -

“…Classification of imbalanced data sets is one of the important researches in Data Mining community, since the data sets in many real-world problems mostly are imbalanced class distribution. …”
Get full text
Get full text

An Integrated Principal Component Analysis And Weighted Apriori-T Algorithm For Imbalanced Data Root Cause Analysis by Ong, Phaik Ling

“…A semiconductor manufacturing case study with Work In Progress data and true alarm data is used to proof the proposed algorithm. …”
Get full text
Get full text
Get full text
Get full text

Fuzzy Soft Set Clustering for Categorical Data by Iwan Tri Riyadi, Yanto, Ani, Apriani, Rofiul, Wahyudi, Cheah, Wai Shiang, Suprihatin, in, Rahmat, Hidayat

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

Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

“…Classification of imbalanced datasets remained a significant issue in data mining and machine learning (ML) fields. This research work proposed a new idea based on the optimization for handling the imbalanced datasets. …”
Get full text
Get full text

ReSTiNet: An efficient deep learning approach to improve human detection accuracy by Shahriar Shakir, Sumi, Dayang Rohaya, Awang Rambli, Mirjalili, Seyedali, Miah, M. Saef Ullah, Muhammad Mudassir, Ejaz

“… • All the necessary steps, algorithms, and mathematical formulas for building the net- work are provided…”
Get full text
Get full text
Get full text

ReSTiNet: An Efficient Deep Learning Approach to Improve Human Detection Accuracy by Sumit, S.S., Rambli, D.R.A., Mirjalili, S., Miah, M.S.U., Ejaz, M.M.

“…The developed ReSTiNet contains fire modules by evaluating their number and position in the network to minimize the model parameters and network size. …”
Get full text
Get full text

Sequential pattern mining using personalized minimum support threshold with minimum items by Alias, Suraya, Razali, Mohd Norhisham, Tan, Soo Fun, Sainin, Mohd Shamrie

“…One of the challenges of Sequential Pattern Mining is finding frequent sequential patterns in a huge click stream data (web logs) since the data has the issue of a very low support distribution.By applying a Frequent Pattern Discovery technique, a sequence is considered as frequent if it occurs more than the minimum support (min sup) threshold value.The conventional method of assuming one min sup value is valid for all levels of k-sequence, may have an impact on the overall results or pattern generation. …”
Get full text
Get full text
Get full text