Search Results - (( based constructive method algorithm ) OR ( process classification learning algorithm ))

An evolutionary based features construction methods for data summarization approach by Rayner Alfred, Suraya Alias, Chin, Kim On

“…In this work, we empirically compare the predictive accuracies of classification tasks based on the proposed feature construction methods and also the existing feature construction methods. …”
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Machine learning for data classification in construction project planning by Lau, Zheng Liang

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Malicious URL Detection with Distributed Representation and Deep Learning by Do N.Q., Selamat A., Lim K.C., Krejcar O.

Image classification based on sparse-coded features using sparse coding technique for aerial imagery: a hybrid dictionary approach by Qayyum A., Saeed Malik A., Saad N.M., Iqbal M., Abdullah M.F., Rasheed W., Abdullah T.A.B.R., Bin Jafaar M.Y.

“…Aerial photography; Aircraft detection; Antennas; Codes (symbols); Discrete cosine transforms; Discrete wavelet transforms; Glossaries; Image classification; Image coding; Image enhancement; Learning algorithms; Learning systems; Object recognition; Remote sensing; Satellite imagery; Satellites; Unmanned aerial vehicles (UAV); Discrete tchebichef transforms; Discriminative features; Finite Ridgelet Transform; Histogram of oriented gradients; Image processing and computer vision; Scale invariant feature transforms; SIFT; Sparse coding; Classification (of information)…”

A framework of modified adaptive neuro-fuzzy inference engine by Hossen, Md. Jakir

“…Neuro-fuzzy inference engine and/or system is knowledge based data processing system and can manage the human reasoning course and create decisions based on uncertainty and imprecise situations. …”
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Speaker identification through feature fusion based deep learning / Rashid Jahangir by Rashid , Jahangir

“…In addition, DNN obtained better classification results compared with the other five machine learning algorithms that were recently utilised in speaker recognition. …”
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Pattern generation through feature values modification and decision tree ensemble construction by Akhand, M. A. H, Rahman, M.M. Hafizur, Murase, K.

“…A number of methods have been investigated for constructing ensemble in which some of them train classifiers with the generated patterns. …”
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Sound quality classification of wood used for Sarawak traditional musical instrument- Sape / Wong Tee Hao by Wong , Tee Hao

“…To address dataset imbalances, Synthetic Minority Oversampling Technique was used, enhancing dataset quality before training 40 machine learning classification algorithms. Among these, the Gaussian-kernel Support Vector Machine stood out, achieving remarkable performance with 88.18% validation and 93.37% test accuracies. …”
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Autism Spectrum Disorder Classification Using Deep Learning by Abdulrazak Yahya, Saleh, Lim Huey, Chern

“…The goal of this paper is to evaluate the deep learning algorithm for people placed in the Autism Spectrum Disorder (ASD) classification. …”
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

“…The problems in applying unsupervised learning/clustering is that this method requires teacher during the classification process and it has to learn independently which may lead to poor classification. …”
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Waste management using machine learning and deep learning algorithms by Sami, Khan Nasik, Amin, Zian Md Afique, Hassan, Raini

“…So, we are proposing an automated waste classification problem utilizing Machine Learning and Deep Learning algorithms. …”
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A Comparative Analysis of Machine Learning and Deep Learning Algorithms for Image Classification by Madanan M., Gunasekaran S.S., Mahmoud M.A.

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Stress mental health symptom assessment mobile application for young adults by Lee, Chun Hoong

“…Before this stage, the KNN algorithm is employed to construct the model using Google Form response data as part of the application development process. …”
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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.

“…The finding showed that AODE algorithm is performed well in term of accuracy and processing time for binary classification towards UNSW-NB15 dataset.…”
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Hybrid signal processing and machine learning algorithm for adaptive fault classification of wind farm integrated transmision line protection by Olufemi, Osaji Emmanuel, Othman, Mohammad Lutfi, Hizam, Hashim, Othman, Muhammad Murtadha, Ammar, Aker Elhadi Emhemed Alhaaj, Okeke, Chidiebere Akachukwu, Onuabuchi, Nwagbara Samuel

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Using KNN algorithm for classification of textual documents by Moldagulova A., Sulaiman R.B.

“…Classification (of information); Information retrieval systems; Learning systems; Nearest neighbor search; Tellurium compounds; Text processing; Automated classification; Exponential growth; K nearest neighbor (KNN); k-NN algorithm; Text classification; Textual documents; Two sources; Learning algorithms…”

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

“…The objective of this study is to suggest the potential classification model for talent forecasting throughout some experiments using SVM learning algorithm. …”
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Enhancing Classification Algorithms with Metaheuristic Technique by Cokro, Nurwinto, Tri Basuki, Kurniawan, Misinem, ., Tata, Sutabri, Yesi Novaria, Kunang

“…Implementing this process uses classification algorithms such asNaïve Bayes, Support Vector Machine,and Random Forest. …”
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Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images by Adil Humayun, Khan

“…This process consists of four steps: pre-processing, segmentation, feature extraction, and classification. …”
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The formulation of a transfer learning pipeline for the classification of the wafer defects by Lim, Shi Xuen

“…However, limitations such as robustness and difficulty in setting up the parameters required for image processing algorithm encourages the investigation in using Deep learning classification in detecting the wafer defects. …”
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