AI is transforming every industry, from medicine to film to finance. So, why not use it to study one of the world's most ...

Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...

algorithm and the extreme learning machine (ELM), is proposed in this study, and the stresses of AZ80 magnesium alloy are predicted by the model through a 812-record dataset. The predicting results ...

In this paper, a CM method that is based on the KNN regression method and bagging ensemble strategy is proposed. The proposed method is validated by SCADA data collected from a field WT. The results ...

College of Computing and Information Sciences, University of Technology and Applied Sciences, P.O. Box: 135, Suhar 311, Sultanate of Oman, Oman ...

tweet_classification/ │ ├── data/ # CSV dataset files │ └── labeled_data.csv │ ├── models/ # Contains each model's training function │ ├── knn_model.py │ ├── svm_model.py │ ├── ...

Abstract: Identifying handwritten words poses a complicated problem owing to the variances in handwriting styles and the possible noise and distortions present in the data. The performance of used ...

Then they trained a collection of machine learning surrogate models for each radiation detector and used an offline optimization algorithm to determine the voltage settings for reducing radiation ...