Search Results - (( based interaction method algorithm ) OR ( data classification using algorithm ))

Autism Spectrum Disorder Classification Using Deep Learning by Abdulrazak Yahya, Saleh, Lim Huey, Chern

“…Finally, the effectiveness of the algorithm is evaluated based on the accuracy performance. …”
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EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter by Woon, W.C., Yahya, N., Badruddin, N.

“…This is taking advantage on the discriminative feature provided by both methods, statistical and CSP filter, which is expected to increase the accuracy of the eye state classification algorithm. The process of developing the EEG eye state classification algorithm, includes data extraction, pre-processing, data normalization, feature extraction, feature selection and classification are detailed out in this paper. …”
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EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter by Woon, W.C., Yahya, N., Badruddin, N.

“…This is taking advantage on the discriminative feature provided by both methods, statistical and CSP filter, which is expected to increase the accuracy of the eye state classification algorithm. The process of developing the EEG eye state classification algorithm, includes data extraction, pre-processing, data normalization, feature extraction, feature selection and classification are detailed out in this paper. …”
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Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool by Nurshafiqa Saffah, Mohd Sharif

“…From the data analysis using WEKA software, the production rules classifier (PART) is found to be the most accurate classification algorithm in classifying the emotion which yields the highest precision percentage of 99.6% compared to J48 (99.5%) and Naïve Bayes (96.2%). …”
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An Empirical Evaluation of Artificial Intelligence Algorithm for Hand Posture Classification by Hussain, A., Hussain, S.S., Uddin, M.M., Zubair, M., Kumar, P., Umair, M.

“…In this study, exhaustive empirical research of the machine learning algorithm for hand posture classification has been established. …”
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Genetic ensemble biased ARTMAP method of ECG-Based emotion classification by Loo, C.K., Liew, W.S., Sayeed, M.S.

“…Classification performance can be improved by implementing a reliability threshold for training data. …”
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Landslide susceptibility mapping using decision-tree based chi-squared automatic interaction detection (CHAID) and logistic regression (LR) integration by Althuwaynee, Omar F., Pradhan, Biswajeet, Ahmad, Noordin

“…This article uses methodology based on chi-squared automatic interaction detection (CHAID), as a multivariate method that has an automatic classification capacity to analyse large numbers of landslide conditioning factors. …”
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A novel ensemble decision tree-based CHi-squared Automatic Interaction Detection (CHAID) and multivariate logistic regression models in landslide susceptibility mapping by Althuwaynee, Omar F., Pradhan, Biswajeet, Park, Hyuck Jin, Lee, Jung Hyun

“…An ensemble algorithm of data mining decision tree (DT)-based CHi-squared Automatic Interaction Detection (CHAID) is widely used for prediction analysis in variety of applications. …”
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Implementation of welch pre-processing in SVM algorithm for improved accuracy on EEG data by Hariyady Hariyady, Ag Asri Ag Ibrahim, Jason Teo, Muhammad Balya Firjaun Barlaman, Muhammad Aulanas Bitaqwa, Azhana Ahmad, Fouziah Md Yassin, Carolyn Salimun, Ng, Giap Weng

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A study on component-based technology for development of complex bioinformatics software by Ali Shah, Zuraini, Deris, Safaai, Othman, Muhamad Razib, Zakaria, Zalmiyah, Saad, Puteh, Hassan, Rohayanti, Muda, Mohd. Hilmi, Kasim, Shahreen, Roslan, Rosfuzah

“…The second layer uses discriminative SVM algorithm with a state-of-the-art string kernel based on PSI-BLAST profiles that is used to leverage the unlabeled data. …”
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Improving multi-resident activity recognition in smart home using multi label classification with adaptive profiling by Mohamed, Raihani

“…On top of that, data association and algorithm modification inherit drawbacks on recognizing the residents and interactions of multi-resident complex activities. …”
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Informative top-k class associative rule for cancer biomarker discovery on microarray data by Ong, Huey Fang, Mustapha, Norwati, Hamdan, Hazlina, Rosli, Rozita, Mustapha, Aida

“…Nevertheless, more studies are needed on improving the predictability of the discovered gene biomarkers, as well as their reproducibility and interpretability, to qualify them for clinical use. This paper proposes an informative top-k class associative rule (iTCAR) method in an integrative framework for identifying candidate genes of specific cancers. iTCAR introduces an enhanced associative classification algorithm that integrates microarray data with biological information from gene ontology, KEGG pathways, and protein-protein interactions to generate informative class associative rules. …”
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Informative top-k class associative rule for cancer biomarker discovery on microarray data by Ong, Huey Fang, Mustapha, Norwati, Hamdan, Hazlina, Rosli, Rozita, Mustapha, Aida

“…Nevertheless, more studies are needed on improving the predictability of the discovered gene biomarkers, as well as their reproducibility and interpretability, to qualify them for clinical use. This paper proposes an informative top-k class associative rule ( i TCAR) method in an integrative framework for identifying candidate genes of specific cancers. i TCAR introduces an enhanced associative classification algorithm that integrates microarray data with biological informa- tion from gene ontology, KEGG pathways, and protein-protein interactions to generate informative class associative rules. …”
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Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients by Moghbel, Mehrdad

“…The proposed method is based on a hybrid method integrating random walkers algorithm with integrated priors and particle swarm optimized spatial fuzzy c-means (FCM) algorithm with level set method and AdaBoost classifier. …”
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Study of hand gesture recognition using impulse radio ultra wideband (IRUWB) radar sensor by Terence Jerome Daim

“…The developed algorithms interpret raw IR-UWB radar sensor data and associate it with specific hand gestures, addressing the core objective of gesture recognition. …”
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Development of collision avoidance warning system for heavy vehicles featuring adaptive minimum safe distance / Airul Sharizli Abdullah by Airul Sharizli, Abdullah

“…To represent the adaptive minimum safe distance which will be used in activation algorithm for CAWS, the new distance-based CAWS model, namely Minimum Safe Distance Gap (MSDG) is introduced. …”
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A Review on the Development of Indonesian Sign Language Recognition System by Jasni, Mohamad Zain, Sutarman, na, Mazlina, Abdul Majid

“…Effective algorithms for segmentation, matching the classification and pattern recognition have evolved. …”
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Predictive analytics for the sentiment of malaysian place of interest using machine learning models by Qiryn Adriana, Kharul Zaman

“…The focus of this study is to conduct Natural Language Processing (NLP) on tweets and make a better classification of sentiment using Malaya. Furthermore, this study also trains three machine learning algorithms to predict the sentiment of textual data. …”
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Identifying the correct articulation point of a Quranic letters of the throat (al-halqu) makhraj by Othman, Ahmad Al Baqir, Ahmad, Salmiah, Badron, Khairayu, Altalmas, Tareq M. K.

“…Data was trained using an improved deep learning Convolutional Neural Network (CNN) classification model. …”
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A Review: Recent Automatic Algorithms for the Segmentation of Brain Tumor MRI by Rafi, A., Khan, Z., Aslam, F., Jawed, S., Shafique, A., Ali, H.

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