Search Results - (( data classification learning algorithm ) OR ( basic classifications learning algorithm ))

Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

“…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
Get full text
Get full text

The Role of Machine Learning and Deep Learning Approaches for the Detection of Skin Cancer by Tehseen Mazhar, Inayatul Haq, Allah Ditta, Syed Agha Hassnain Mohsan, Faisal Rehman, Imran Zafar, Jualang Azlan Gansau, Lucky Poh Wah Goh

“…The development of ML algorithms in dermatology has been supported lately regarding links to digital data processing (e.g., electronic medical records, Image Archives, omics), quicker computing and cheaper data storage. …”
Get full text
Get full text
Get full text

Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
Get full text
Get full text

Review of deep convolution neural network in image classification by Al-Saffar, Ahmed Ali Mohammed, Tao, Hai, Mohammed, Ahmed Talab

“…The convolution neural network model trained by the deep learning algorithm has made remarkable achievements in many large-scale identification tasks in the field of computer vision since its introduction. …”
Get full text
Get full text
Get full text

Modelling of clinical risk groups (CRGs) classification using FAM by Mohd. Asi, Salina, Saad, Puteh

“…FAM is a fast learning algorithm and used less epoch training [4]. …”
Get full text
Get full text

Identification model for hearing loss symptoms using machine learning techniques by Nasiru Garba Noma

“…This research presents an efficient way to facilitate the hearing loss symptoms diagnosis process by designing a symptoms identification model that efficiently identify hearing loss symptoms based on air and bone conduction pure-tone audiometry data. The model is implemented using both unsupervised and supervised machine learning techniques in the form of Frequent Pattern Growth (FP-Growth) algorithm as feature transformation method and multivariate Bernoulli naïve Bayes classification model as the classifier. …”
Get full text
Get full text
Get full text
Get full text

Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant by Morshidi, Malik Arman

“…Results of studying color segmentation using machine-learning algorithm and color space analysis is presented in this thesis. …”
Get full text
Get full text

Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning by Solihin M.I., Yanto, Hayder G., Maarif H.A.-Q.

Improved normalization and standardization techniques for higher purity in K-means clustering by Dalatu, Paul Inuwa, Fitrianto, Anwar, Mustapha, Aida

“…The K-means algorithm is a famous and fast technique in non-hierarchical cluster algorithms. …”
Get full text
Get full text
Get full text

Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition by Ali Adlan, Hanan Hassan

“…The neural network learns the rough set’s upper and lower approximations as feature extractors simultaneously with classification. …”
Get full text
Get full text

A stacked ensemble deep learning model for water quality prediction / Wong Wen Yee by Wong , Wen Yee

“…Therefore, this paper aims to explore the use of ensemble and deep learning techniques to simplify the classification process of imbalanced data. …”
Get full text
Get full text
Get full text

Image Splicing Detection With Constrained Convolutional Neural Network by Lee, Yang Yang

“…The constrained layer enables the CNN model to learn the required features directly from ubiquitous image input and then performs classification. …”
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

Students Activity Recognition By Heart Rate Monitoring In Classroom Using K-means Classification by Hadi Helmi Md Zuraini, Rimuljo Hendradi, Army Justitia, Waidah Ismail

Get full text

Integrated artificial intelligence-based classification approach for prediction of acute coronary syndrome by Salari, Nader

“…Performance evaluation of the proposed model were conducted by comparing 13 well-known classification models based on various commonly used evaluation criteria on seven data sets (ACSEKI data set as well as six data sets taken from the University of California Irvine (UCI) machine-learning repository). …”
Get full text
Get full text
Get full text

Hybrid Neural Network With K-Means For Forecasting Response Candidate In Direct Marketing by Ramadhan, Rakhmat Sani

“…The data was collected from the Machine Learning Repository Dataset in the University of California Irvine (UCI).This experiment compares hybrid K-Means + NN with basic NN. …”
Get full text
Get full text
Get full text
Get full text

Text-based emotion prediction system using machine learning approach by Ahmad Fakhri, Ab. Nasir, Eng, Seok Nee, Chun, Sern Choong, Ahmad Shahrizan, Abdul Ghani, Anwar, P. P. Abdul Majeed, Asrul, Adam, Mhd, Furqan

“…Therefore, four supervised machine learning classification algorithms such as Multinomial Naïve Bayes, Support Vector Machine, Decision Trees, and kNearest Neighbors were investigated. …”
Get full text
Get full text
Get full text
Get full text

Mean of correlation method for optimization of affective states detection in children by Rusli, Nazreen, Sidek, Shahrul Na'im, Md Yusuf, Hazlina, Ishak, Nor Izzati

“…At the moment, most of the studies on classification of affective states for children focus on visual observations and physiological cues, where all data collection for measuring physiological signals are contact-based and invasive. …”
Get full text
Get full text
Get full text
Get full text

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

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