The year 2024 is the time when most manual things are being automated with the assistance of Machine Learning algorithms. You’d be surprised at the growing number of ML algorithms that help play chess ...

On the other side, machine learning algorithms ... (GP), kNN, (LR), Linear Discriminant, Support Vector Machine, Voting classifiers, Multi-Classifier Network (MCN), Gradient Boosted Trees (GBTs), ...

Given a new image of a concrete structure, use the trained KNN model to predict the length of the cracks. The supervised learning algorithm Support Vector Machine (SVM), which ... to the ...

Validation sets are used to select the best architecture ... random forest, KNN, ANN, and decision tree. Predicting property prices is a critical challenge in the real estate market, and the choice of ...

Abstract: Increasingly, machine-learning algorithms ... architectures for the K-Nearest Neighbor (KNN) classification algorithm. Each ASIP is developed using Cadence Tensilica tools and represents a ...

In contrast to the Recurrent Neural Networks (RNNs) that had begun to dominate ML research in the CUDA era, Transformer architecture ... (KNN) is a lean algorithm that still features prominently ...

The schematic diagram for the ANN used in this work is presented in Figure 2. 4. Results and Discussion With the goal of assessing the performance of the different ML algorithms, we have used four ...