The last chapter of the three-part series on Evolutionary Feature Selection with Big datasets. We will address some fundamental design aspects of a Genetic Algorithm (GA) and commonly chosen options, to then move on to the CHC algorithm and a distributed approach for Feature Selection.
This is the second chapter of a three-part series on Evolutionary Feature Selection with Big datasets. We will start where we left off, namely with a review of existing metaheuristics with special focus on Genetic Algorithms.
When we want to fit a Machine Learning (ML) model to a big dataset, it is often recommended to carefully pre-process the input data in order to obtain better results.
Where can you find Stratio at? We can’t believe it’s already October! You might already be planning your winter holidays and festive meals, but we hope there is still time to get to know more about Generative AI Data Fabric. We will be attending some more industry events this month. Why not stop by our booth to see Stratio Generative AI Engine for Enterprise in action and understand how Stratio Data Fabric product can automate…
This post will focus on a class of metaheuristics known as Swarm Intelligence. The most amazing feature of these algorithms is their ability to solve complex problems by a set of cooperative agents posing very simple intelligence.
