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An improved algorithm for iris classification by using support vector machine and binary random machine learning by Kamarulzalis, Ahmad Haadzal

“…In machine learning, there are three type of learning branch that can used in classification procedures for data mining. …”
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Utilizing artificial bee colony algorithm as feature selection method in Arabic text classification by Hijazi, Musab, Zeki, Akram M., Ismail, Amelia Ritahani

“…Support Vector Machine and Naïve Bayes classifiers were used as a fitness function for the ABC algorithm. …”
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A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani by Mahmoud Reza, Saybani

“…Various data mining techniques are being used by researchers of different domains to analyze data and extract valuable information from a data set for further use. …”
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A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules by Rizauddin, Saian

“…Benchmark data sets from various fields were used to test the proposed algorithms. …”
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Computational Technique for an Efficient Classification of Protein Sequences With Distance-Based Sequence Encoding Algorithm by Iqbal, M.J., Faye, I., Said, A.M.D., Samir, B.B.

“…The performance of the proposed technique is validated using some of the best performing classifiers implemented previously for protein sequence classification. …”
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Anomaly detection in ICS datasets with machine learning algorithms by Mubarak, Sinil, Habaebi, Mohamed Hadi, Islam, Md Rafiqul, Abdul Rahman, Farah Diyana, Tahir, Mohammad

“…The features of flow-based network traffic are extracted for behavior analysis with port-wise profiling based on the data baseline, and anomaly detection classification and prediction using machine learning algorithms are performed.…”
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Intent-IQ: customer’s reviews intent recognition using random forest algorithm by Mazlan, Nur Farahnisrin, Ibrahim Teo, Noor Hasimah

“…Two machine learning model is chosen to build the classification models which are Random Forest (RF) algorithm and Multinomial Naïve Bayes (MNB) algorithm. …”
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Enhancement of new smooth support vector machines for classification problems by Santi Wulan, Purnami

“…The smooth function is used to replace the plus function to obtain a smooth support vector machine (SSVM). …”
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Hand gesture recognition for autism diagnosis using Support Vector Machine (SVM) Algorithm / Muhammad Asyraf Mohamad Zain by Mohamad Zain, Muhammad Asyraf

“…To counter this problem, a system has been proposed to detect the hand gesture using one of the machine learning technique which is Support Vector Machine (SVM) Algorithm. …”
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On equivalence of FIS and ELM for interpretable rule-based knowledge representation by Wong S.Y., Yap K.S., Yap H.J., Tan S.C., Chang S.W.

Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification by Myaser, Jwan

“…Nevertheless, AC is not required for LCM if the original multi-spectral image is used. The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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Named entity recognition using a new fuzzy support vector machine. by Mansouri, Alireza, Affendy, Lilly Suriani, Mamat, Ali

“…In our method we have employed Support Vector Machine as one of the best machine learning algorithm for classification and we contribute a new fuzzy membership function thus removing the Support Vector Machine’s weakness points in NER precision and multi classification. …”
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Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms by Choong, Chun Sern

“…The ensemble learning technique, changes of activation function in Neural Network as well as the unsupervised learning (k-means clustering algorithm and Friis Transmission Equation) was also applied to classify the multiclass classification in pallet-level. …”
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Improvement on rooftop classification of worldview-3 imagery using object-based image analysis by Norman, Masayu

“…Then, the classifier (support vector machine (SVM) and data mining (DM) algorithm, decision tree (DT) were applied on each fusion image and their accuracy were evaluated. …”
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Agarwood oil quality classification using one versus all strategies in multiclass on SVM model / Aqib Fawwaz Mohd Amidon … [et al.] by Mohd Amidon, Aqib Fawwaz, Mahabob, Noratikah Zawani, Ismail, Nurlaila, Mohd Yusoff, Zakiah, Taib, Mohd Nasir

“…Support vector machine (SVM) has been chosen as a main model and for the specific function algorithm was multiclass function. …”
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Alternative Relative Discrimination Criterion Feature Ranking Technique for Text Classification by ABDULKAREM ALSHALIF, SARAH, SENAN, NORHALINA, SAEED, FAISAL, WAD GHABAN, WAD GHABAN, IBRAHIM, NORAINI, MUHAMMAD AAMIR, MUHAMMAD AAMIR, WAREESA SHARIF, WAREESA SHARIF

“…The use of text data with high dimensionality affects classifier performance. …”
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Development and usage of self-organising maps in high energy physics analysis with high performance computing / Mohd Adli Md Ali by Mohd Adli , Md Ali

“…At the present time, it is regarded as one of the primary machine learning techniques to perform unsupervised clustering analysis on a large variety of huge data. …”
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A novel framework for potato leaf disease detection using an efficient deep learning model by Mahum, R., Munir, H., Mughal, Z.-U.-N., Awais, M., Sher Khan, F., Saqlain, M., Mahamad, S., Tlili, I.

“…Moreover, the usage of the reweighted cross-entropy loss function makes our proposed algorithm more robust as the training data is highly imbalanced. …”
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A novel framework for potato leaf disease detection using an efficient deep learning model by Mahum, R., Munir, H., Mughal, Z.-U.-N., Awais, M., Sher Khan, F., Saqlain, M., Mahamad, S., Tlili, I.

“…Moreover, the usage of the reweighted cross-entropy loss function makes our proposed algorithm more robust as the training data is highly imbalanced. …”
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Data Mining for Building Neural Protein Sequence Classification Systems with Improved Performance by Wang, Dianhui, Lee, Nung Kion, Dillon, Tharam S.

“…Neural network approaches, while reasonably accurate at classification, give no information ahout the relationship between the unseen case and the classified items that is useful to biologist. In contrast, in this paper we use a generalized radial basis function (GRBF) neural network architecture 'that generates fuzzy classification rules that could he used for further knowledge discovery. …”
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