3 Results 3.1 KDDC framework: classification of cell heterogeneity based on amino acid sequence similarity We propose a novel framework that integrates k-mer cutting, dataset screening, dimensionality ...

With the development of computers, artificial intelligence, and cognitive science, engagement in deep communication between humans and computers has become increasingly important. Therefore, affective ...

This paper presents a new concept of building classification-type loss for regression sample based on conversion between regression and classification problems used in Support Vector Regression (SVR).

Decision Trees are a popular supervised machine learning algorithm used for both classification and regression tasks. They mimic human decision-making processes by creating a tree-like model of ...

The SVM algorithm can simplify complex classification and regression tasks when handling small samples, thereby improving the efficiency and accuracy of the algorithm.

Here, we develop a claims-based classification algorithm that is able to distinguish between type 1 and type 2 myocardial infarction with excellent discrimination.

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