Search Results - (( pattern machine algorithm ) OR ( ((peer learning) OR (e learning)) algorithm ))

A Review of Unsupervised Machine Learning Frameworks for Anomaly Detection in Industrial Applications by Usmani, U.A., Happonen, A., Watada, J.

“…Without human input, these algorithms discover patterns or groupings in the data. …”
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Analysis of banana plant health using machine learning techniques by Thiagarajan, Joshva Devadas, Kulkarni, Siddharaj Vitthal, Jadhav, Shreyas Anil, Waghe, Ayush Ashish, Raja, S.P., Rajagopal, Sivakumar, Poddar, Harshit, Subramaniam, Shamala

“…Automated systems that integrate machine learning and deep learning algorithms have proven to be effective in predicting diseases. …”
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Prediction of stroke disease using machine learning techniques / Syarifah Adilah Mohamed Yusoff ... [et al.] by Mohamed Yusoff, Syarifah Adilah, Warris, Saiful Nizam, Abu Bakar, Mohd Saifulnizam, Kadar, Rozita

“…This study has investigated five commonly used machine learning algorithm to be constructed as potential models for predicting stroke dataset. …”
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Market prices trend forecasting supported by Elliott Wave's theory by Vantuch, T., Zelinka, I., Vasant, P.

“…The combination of ML algorithms and EW pattern detector achieved significantly higher performance compare to the ML algorithms only.…”
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Lexicon-based and immune system based learning methods in Twitter sentiment analysis by Jantan, Hamidah, Drahman, Fatimatul Zahrah, Alhadi, Nazirah, Mamat, Fatimah

“…The aim of this article attempts to study the potential of this method in text classification for sentiment analysis.This study consists of three phases; data preparation; classification model development using three selected Immune System based algorithms i.e. Negative Selection algorithm (NSA), Clonal Selection algorithm (CSA) and Immune Network algorithm (INA); and model analysis. …”
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A Truly Online Learning Algorithm using Hybrid Fuzzy ARTMAP and Online Extreme Learning Machine for Pattern Classification by Wong S.Y., Yap K.S., Yap H.J., Tan S.C.

“…Algorithms; Benchmarking; E-learning; Knowledge acquisition; Learning systems; Pattern recognition; Bench-mark problems; Efficient learning; Extreme learning machine; Fuzzy ARTMAP; Generalization performance; Online learning; Online learning algorithms; Online sequential extreme learning machine; Learning algorithms…”

Integrated Features by Administering the Support Vector Machine of Translational Initiations Sites in Alternative Polymorphic Context by Nanna Suryana, Herman, Burairah, Hussin

“…In this study, the discriminative approach in particular support vector machines (SVM) is employed to recognize the studied TIS patterns. …”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification by Chong, Hou Ming, Yin Yap, Xien, Seng Chia, Kim

“…This study proposes a system that can classify tomato plant health into five categories of healthy, early blight, late blight, bacterial spot, and yellow leaf curl virus based on their leaves using deep learning algorithms as feature extractors. Five different pre-trained deep learning algorithms (i.e. …”
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Alternate methods for anomaly detection in high-energy physics via semi-supervised learning by Md. Ali, Mohd. Adli, Badrud’din, Nu’man, Abdullah, Hafidzul, Kemi, Faiz

“…We tested the algorithms’ capability to create distinct anomalous patterns in the presence of BSM samples and also compare their classification output metrics to the Isolation Forest (ISF), a well-known anomaly detection algorithm. …”
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Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation by Mat Jani H., Lee S.P.

Subjects: “…Knuth-Morris-Pratt (KMP) pattern matching algorithm…”

A novel hybrid photovoltaic current prediction model utilizing singular spectrum analysis, adaptive beluga whale optimization, and improved extreme learning machine by Mohammed Ridha, Hussein, Ahmadipour, Masoud, Alghrairi, Mokhalad, Hizam, Hashim, Mirjalili, Seyedali, Zubaidi, Salah L., Mohammed S, Marwa Y.

“…Ultimately, the hyperparameters of the IELM model are optimized utilizing ABWO algorithm. The numerical experimental results demonstrated that the ABWO algorithm beat all other optimization methods and could solve the majority of the benchmark functions. …”
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Identifying Cyberspace Users� Tendency in Blog Writing Using Machine Learning Algorithms by AbuSalim, S.W.G., Mostafa, S.A., Mustapha, A., Ibrahim, R., Wahab, M.H.A.

“…In this paper, we use an existing data set from previous research, which has 100 records of data, and manipulate the data by applying three machine learning algorithms for implementing classification and regression tasks. …”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification by Hou Ming Chong, Hou Ming Chong, Xien Yin Yap, Xien Yin Yap, Kim Seng Chia, Kim Seng Chia

“…This study proposes a system that can classify tomato plant health into five categories of healthy, early blight, late blight, bacterial spot, and yellow leaf curl virus based on their leaves using deep learning algorithms as feature extractors. Five different pre-trained deep learning algorithms (i.e. …”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification by Hou Ming Chong, Hou Ming Chong, Xien Yin Yap, Xien Yin Yap, Kim Seng Chia, Kim Seng Chia

“…This study proposes a system that can classify tomato plant health into five categories of healthy, early blight, late blight, bacterial spot, and yellow leaf curl virus based on their leaves using deep learning algorithms as feature extractors. Five different pre-trained deep learning algorithms (i.e. …”
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Effects of Different Pre-Trained Deep Learning Algorithms as Feature Extractor in Tomato Plant Health Classification by Hou Ming Chong, Hou Ming Chong, Xien Yin Yap, Xien Yin Yap, Kim Seng Chia, Kim Seng Chia

“…This study proposes a system that can classify tomato plant health into five categories of healthy, early blight, late blight, bacterial spot, and yellow leaf curl virus based on their leaves using deep learning algorithms as feature extractors. Five different pre-trained deep learning algorithms (i.e. …”
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Investigating optimal smartphone placement for identifying stairs movement using machine learning by Muhammad Ruhul Amin, Shourov, Husman, Muhammad Afif, Toha, Siti Fauziah, Jasni, Farahiyah

“…The data was trained against 6 machine learning algorithms namely Decision Tree, Logistic Regression, Naive Bayes, Random Forest, Neural Networks and KNN. …”
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Automated Nutritional Guidance for Obesity Management: Insights from Machine Learning, Naïve Bayes, Random Forest by A., Rupa, Ch. Akshaya, Reddy, E., Shravya, E., Akshaya, K., Rajasri

“…The system utilizes a combination of machine learning algorithms, nutritional databases, and user input to provide personalized dietary plans aligned with individual health goals, dietary preferences, and lifestyle patterns. …”
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E4ML: Alat untuk pembelajaran perlombongan data by Sainin, Mohd Shamrie, Siraj, Fadzilah

“…However, most of the tool is complicated to be used by the beginner user especially to student.The absence of specific and easy tool was made the student unable to understand the use and applications in this field.This paper discusses the development of the teaching aid tool (software) that consist of several machine learning algorithms for the purpose of explaining data mining processes.With this tool, teaching and learning for such course can be enhanced in order to provide better understanding in data mining and machine learning.…”
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Financial time series predicting using machine learning algorithms by Tiong, Leslie Ching Ow *

“…Thereafter, Artificial Neural Network (ANN) and Support Vector Machine (SVM) algorithms are implemented separately to train with the trend patterns for predicting the movement direction of financial trends. …”
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A machine learning approach to predict the activity of smart home inhabitant by Marufuzzaman M., Tumbraegel T., Rahman L.F., Sidek L.M.