This work includes two high performance recognizers. The SVM based recognizer has an accuracy of 90%. It first applies projection-based algorithm to the input image, then use a pre-trained SVM model ...

In this tutorial, we’ll build on the foundation laid in the “Arduino-Based Solar Power System Using Python & Machine Learning, Part 1” project by exploring how to intelligently select and use machine ...

The “gut–skin axis” has been proposed to play an important role in the development and symptoms of atopic dermatitis. Therefore, we have constructed an interpretable machine learning framework to ...

This project involves the classification of handwritten digits using three different classifiers: Linear Discriminant Analysis (LDA), Support Vector Machines (SVM), and Decision Trees. The goal is to ...

TOC can not only generate gas but also provide the main space for gas storage. The structure of the organic matters within the connected and isolated pore network is essential for gas storage capacity ...

Binary classification algorithms are essential for achieving high accuracy in modelling. Support Vector Machines are popular among data scientists for binary classification tasks. One-vs-Rest and ...

Bayesian Decision Trees provide a probabilistic framework that reduces the instability of Decision Trees while maintaining their explainability. While Markov Chain Monte Carlo methods are typically ...

Generating an immeasurable amount of data has become a need to develop more advanced and sophisticated machine learning techniques. Boosting machine learning is one such technique that can be used to ...