Search Results - (( data classification learning algorithm ) OR ( program implementation a algorithm ))

Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

“…One of the problems addressed by machine learning is data classification. Finding a good classification algorithm is an important component of many data mining projects. …”
Get full text
Get full text

Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif by Jantan, Hamidah, Mat Yusof, Norazmah, Abdul Latif, Mohd Hanapi

“…Support Vector Machine (SVM) is among the popular learning algorithm for classification in soft computing techniques. …”
Get full text
Get full text

Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network by Kang, Miew How

“…First proposed algorithm is the combination of momentum algorithm with adaptive learning rate (ALR) algorithm, and second proposed algorithm is the combination of momentum algorithm with automatic learning rate selection (ALRS) algorithm. …”
Get full text
Get full text

Predicting Student Performance in Object Oriented Programming Using Decision Tree : A Case at Kolej Poly-Tech Mara, Kuantan by Mohd Hanis, Rani, Abdullah, Embong

“…The paper focuses on prediction of student learning performance in object oriented programming course using data mining technique based on a dataset obtained from Kolej Poly-Tech Mara (KPTM), Kuantan. …”
Get full text
Get full text

Kernel methods and support vector machines for handwriting recognition by Ahmad A.R., Khalid M., Yusof R.

“…SVM works by mapping training data for a classification task into a higher dimensional feature space using the kernel function and then finding a maximal margin hyperplane, which separates the mapped data. …”

Spiking Neural Network For Energy Efficient Learning And Recognition by Wong, Yan Chiew, Wang, Ning Lo

“…Common building blocks and techniques used to implement a spiking neural network are investigated to identify design parameters for hardware-based neuron implementations. …”
Get full text
Get full text
Get full text

Raspberry Pi-Based Finger Vein Recognition System Using PCANet by Quek, Ee Wen

“…Factors which impact PCANet are studied to identify the limitations of PCANet. For classification, k-Nearest Neighbours (kNN) with Euclidean distance algorithm is implemented. …”
Get full text
Get full text

Development of deep learning based user-friendly interface for fruit quality detection by Mohd Ali, Maimunah, Hashim, Norhashila

“…The implementation of deep learning algorithms has contributed to various applications related to the detection of fruit quality. …”
Get full text
Get full text
Get full text

Exploring frogeye leaf spot disease severity in soybean through hyperspectral data analysis and machine learning with Orange Data Mining by Ang, Yuhao, Mohd Shafri, Helmi Zulhaidi, Al-Habshi, Mohammed Mustafa

“…Objectives: The main objective of the study is to classify the severity level of FLS disease in soybean using hyperspectral reflectance data and machine learning algorithms. Materials and Methods: We used hyperspectral reflectance data from healthy and FLS of soybeans. …”
Get full text
Get full text
Get full text

Propositional satisfiability method in rough classification modeling for data mining by Abu Bakar, Azuraliza

“…The models involved a theoretical formalism of the discemibility relation of a decision system (DS) into an Integer Programming (IP) model. …”
Get full text
Get full text

AI chatbot system for educational institutions by Tan, Hui Hui

“…This project presents the design and development of an advanced chatbot system powered by deep learning algorithms for intent classification. The chatbot's primary goal is to facilitate effective communication and support for users, particularly students inquiring about admission processes. …”
Get full text
Get full text

Problem restructuring in interger programming for reduct searching by Ungku Chulan, Ungku Azmi Iskandar

“…Standard Integer Programming / Decision Related Integer Programming (SIP/DRIP) is a reduct searching system that finds the reducts in an information system. …”
Get full text
Get full text

Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

“…Whereas for supervised learning method, it requires teacher or prior data (i.e. large, prohibitive and labelled training data) during classification process which in real life, the cost of obtaining sufficient labelled training data is high. …”
Get full text
Get full text

Chili crop segregation system design and development strategies by Wan Daud, Wan Mohd Bukhari, Abdul Aziz, Mohd Fareezuan, Ahmad Izzuddin, Tarmizi, Norasikin, Mohd Adili, Abdul Rasid, Ahmad Fuad, Wakhi Anuar, Nur Farah Bazilah, M. N. Sukhaimie

“…The image data taken from chili samples can be trained by using Learning Algorithm in the MATLAB program. …”
Get full text
Get full text
Get full text

Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

“…In data mining, classification learning is broadly categorized into two categories; supervised and unsupervised. …”
Get full text
Get full text
Get full text

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

“…Feature selection and classification are widely utilized for data analysis. …”
Get full text
Get full text
Get full text

Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach by Moheb Pour, Majid Reza

“…The two algorithms were compared, and the proposed algorithm was found to be able to both learn and classify quickly. …”
Get full text
Get full text

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

“…Two different models for learning in data sets were proposed based on two different reduction algorithms. …”
Get full text
Get full text

Performances of machine learning algorithms for binary classification of network anomaly detection system by Nawir, M., Amir, A., Lynn, O.B., Yaakob, N., Ahmad, R.B.

“…Moreover, network anomaly detection using machine learning faced difficulty when dealing the involvement of dataset where the number of labelled network dataset is very few in public and this caused many researchers keep used the most commonly network dataset (KDDCup99) which is not relevant to employ the machine learning (ML) algorithms for a classification. …”
Get full text
Get full text
Get full text

Comparative study of machine learning algorithms in data classification by Tan, Kai Jun

“…This research conducts a comparative study of various machine learning algorithms for dataset classification to identify the most accurate and reliable classifier. …”
Get full text
Get full text