Tag: BCOM214 Research Methodology

In machine learning, backpropagation (backprop, BP) is a widely used algorithm for training feedforward neural networks. Generalizations of backpropagation exist for other artificial neural networks …

The development of the perceptron was a big step towards the goal of creating useful connectionist networks capable of learning complex relations between inputs and …

Convolutional Layers Convolutional layers are the major building blocks used in convolutional neural networks. A convolution is the simple application of a filter to an …

Association rule learning is a type of unsupervised learning technique that checks for the dependency of one data item on another data item and maps …

This clustering method classifies the information into multiple groups based on the characteristics and similarity of the data. Its the data analysts to specify the …

Density-Based Clustering method is one of the clustering methods based on density (local cluster criterion), such as density-connected points. The basic ideas of density-based clustering …

In statistics, nonlinear regression is a form of regression analysis in which observational data are modelled by a function which is a nonlinear combination of …

Supervised learning, the computer is taught by example. It learns from past data and applies the learning to present data to predict future events. In …

K-Nearest Neighbors (KNN) is a non-parametric machine learning algorithm used for both classification and regression tasks. KNN is an instance-based algorithm that is widely used …