Machine learningData MiningNeural NetworkK-fold Cross ValidationAccuracyDiabetes is a disease that has no permanent cure; hence early detection is required. Data mining, machine learning (ML) algorithms, and Ne
The algorithms and techniques deployed in machine learning (ML) can be framed within a more general process known as knowledge discovery in databases or simply data mining. Some of these techniques were described more than 50 years ago [1], however in recent years interest in and about them...
There are three key issues about online classification: observation window size, feature selection, and classification algorithms.In this paper, by collecting five types of typical network flow data as the experiment sample data, the authorsfound observation window size 7 is the best for the sample...
Machine learning algorithms can be used for the prediction of nonnative sound classification based on crosslinguistic acoustic similarity. To date, very few linguistic studies have compared the classification accuracy of different algorithms. This study aims to assess how well machines align with human ...
Machine learning algorithms only depend on the training data to predict the outputs; hence, we can detect the symbol even without the use of cyclic prefix or channel estimation which can save a lot of time and data if the input data is large. A comparative study on the performance of ...
Previous studies of Brain Computer Interfaces (BCI) based on scalp electroencephalography (EEG) have demonstrated the feasibility of decoding kinematics for lower limb movements during walking. In this computational study, we investigated offline decodin
we treat the problem as a text classification challenge. We leverage machine learning algorithms and natural language processing techniques to analyze and classify the text data of the issues. By applying these techniques, we are able to extract relevant information from the issue descriptions, such ...
we employ ensemble methods that leverage a diverse range of machine-learning algorithms. To evaluate the effectiveness of our system, we employ widely recognized metrics such as accuracy, precision, recall, and F1-score which serve as indicators of its performance. To further refine our predictions...
However, the research about a comparison of different machine learning methods is rare; particularly, a comparison of the NN, Extreme Gradient Boosting (XGBoost3), and Light Gradient Boosting Machine (LightGBM4) lacks. A study about the latter two machine learning algorithms in petroleum engineering...
1.2. Machine learning algorithm theory 1.2.1. Naive Bayes Naive Bayes (NB) is a well known statistical learning algorithm recommended as a base level classifier for comparison with other algorithms (Guyon, 2009, Henery, 1994). NB estimates class-conditional probabilities by “naively” assuming th...