Search Results - pattern detection ((using algorithm) OR (((mining algorithm) OR (learning algorithm))))
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1
An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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2
Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan
Published 2020“…In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
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3
Effective mining on large databases for intrusion detection
Published 2014“…Results show that higher detection rate is achieved when using apriori algorithm on the proposed dataset. …”
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4
A Review of Unsupervised Machine Learning Frameworks for Anomaly Detection in Industrial Applications
Published 2022“…Without human input, these algorithms discover patterns or groupings in the data. …”
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5
Tracking student performance in introductory programming by means of machine learning
Published 2023Conference Paper -
6
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Features selection process can be considered a problem of global combinatorial optimization in machine learning. Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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7
A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data
Published 2023“…Overall, most methods have shown an excellent ability to tackle the curse of dimensionality and multivariate features to perform anomaly detection. Moreover, a comparison of each algorithm for anomaly detection is also provided to produce a better algorithm. …”
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8
A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data
“…Overall, most methods have shown an excellent ability to tackle the curse of dimensionality and multivariate features to perform anomaly detection. Moreover, a comparison of each algorithm for anomaly detection is also provided to produce a better algorithm. …”
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9
A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data
Published 2023“…Overall, most methods have shown an excellent ability to tackle the curse of dimensionality and multivariate features to perform anomaly detection. Moreover, a comparison of each algorithm for anomaly detection is also provided to produce a better algorithm. …”
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10
A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data
Published 2023“…Overall, most methods have shown an excellent ability to tackle the curse of dimensionality and multivariate features to perform anomaly detection. Moreover, a comparison of each algorithm for anomaly detection is also provided to produce a better algorithm. …”
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11
A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data
Published 2023“…Overall, most methods have shown an excellent ability to tackle the curse of dimensionality and multivariate features to perform anomaly detection. Moreover, a comparison of each algorithm for anomaly detection is also provided to produce a better algorithm. …”
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12
A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data
Published 2023“…Overall, most methods have shown an excellent ability to tackle the curse of dimensionality and multivariate features to perform anomaly detection. Moreover, a comparison of each algorithm for anomaly detection is also provided to produce a better algorithm. …”
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13
A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data
Published 2023“…Overall, most methods have shown an excellent ability to tackle the curse of dimensionality and multivariate features to perform anomaly detection. Moreover, a comparison of each algorithm for anomaly detection is also provided to produce a better algorithm. …”
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14
A new model for iris data set classification based on linear support vector machine parameter's optimization
Published 2020“…Data mining is known as the process of detection concerning patterns from essential amounts of data. …”
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15
Bat Algorithm for Complex Event Pattern Detection in Sentiment Analysis
Published 2021“…Thus, this study proposed a Bat Algorithm (BA) to address the complex learning structure of DBN in detecting sentiment patterns. …”
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16
The application of neural network data mining algorithm into mixed pixel classification in geographic information system environment
Published 2007“…This , paper discusses the development of data mining and pattern recognition algorithm to handle the complexity of hyperspectral remote sensing images in Geographical Information Systems environment. …”
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17
Detecting Critical Least Association Rules In Medical Databases
Published 2010“…We also employed our scalable algorithm called Significant Least Pattern Growth algorithm (SLP-Growth) to mine the respective association rules. …”
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18
Improvement anomaly intrusion detection using Fuzzy-ART based on K-means based on SNC Labeling
Published 2011“…This paper presents our work to improve the performance of anomaly intrusion detection using Fuzzy-ART based on the K-means algorithm. …”
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19
Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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20
Evaluation of intonation features on emphasized Malay words / Syazwani Nasaruddin
Published 2017“…Activities in this section are, for testing part, 314 words from 2 different speakers are evaluated by using clustering method. WEKA is a set of machine learning algorithm for data mining task. …”
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