What are Genetic Algorithms? Genetic algorithms (GAs) are like nature-inspired computer programs that help find the best solutions to problems. They work by creating lots of possible solutions, like mixing and matching traits, just as animals do. Then, they pick the best ones and repeat the process, making each new generation even better. It’s like evolution in your computer, finding ...

What is Principal Component Analysis? Principal Component Analysis (PCA) is a statistical procedure and an Unsupervised Learning Algorithm for reducing the dimensionality of a data set while retaining as much information as possible. PCA does this by finding a set of new variables, called “Principal Components”, that are linear combinations of the original variables. The principal components are chosen so ...

Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is a density-based clustering algorithm, proposed by Martin Ester et al., 1996. The algorithm finds neighbors of data points, within a circle of radius ε, and adds them into same cluster. For any neighbor point, which its ε-neighborhood contains a predefined number of points, the cluster is expanded to contain its neighbors, ...

Neural Gas network is a competitive Artificial Neural Network (ANN), very similar to Self-Organizing Map (SOM), which is proposed by Martinetz and Schulten, 1991. Neural Gas network can be used to solve unsupervised learning tasks, like clustering, dimensionality reduction, and topology learning. It has many applications in the fields of pattern recognition, data compression, speech recognition, and image segmentation. For ...

Clustering is an unsupervised machine learning task and many real world problems can be stated as and converted to this kind of problems. Clustering is grouping a set of  data objects is such a way that similarity of members of a group (or cluster) is maximized and on the other hand, similarity of members in two different groups, is minimized. ...