Random Forest is a computationally efficient technique that can operate quickly over large
datasets. It has been used in many recent research projects and real-world applications in …

Facial expressions recognition is an important part of the study in man-machine interface.
Principal component analysis (PCA) is an extraction method based on statistical features …

Facial expression recognition plays an important role in the field involving human-computer
interactions. Given the wide use of convolutional neural networks or other neural network …

In order to recognize facial expression accurately, the paper proposed a hybrid method of
principal component analysis (PCA) and local binary pattern (LBP). Firstly, the method of …

Random Forests (RFs) are among the state-of-the-art in machine learning and offer
excellent performance with nearly zero parameter tuning. Remarkably, RFs seem to be …

For most of rock engineering and engineering geology projects, strength and deformability
parameters of intact rocks have crucial importance. However, it is highly challenging to …

Decision trees are popular machine learning models that are simple to build and easy to
interpret. Even though algorithms to learn decision trees date back to almost 50 years, key …

Classification algorithms have been traditionally designed to simultaneously reduce errors
caused by bias as well by variance. However, there occur many situations where low …

Using hierarchies of classes is one of the standard methods to solve multi-class
classification problems. In the literature, selecting the right hierarchy is considered to play a …

In this paper, we give and prove the lower bounds of the Vapnik-Chervonenkis (VC)-
dimension of the univariate decision tree hypothesis class. The VC-dimension of the …