Speed up Machine Learning with Fast Kriging (FKR)
Machine Learning has revolutionized the world, yet expensive computation costs on model trainings are often a large limitation, especially for large data sets or elevated precisions. VMC Consulting offers a new algorithm called Fast Kriging (FKR), which allows to train models with the high precision of Kriging at a speed 100+ times faster, without compromising precision, for any data set size.
Machine Learning has become a vital part of our society in almost all fields of human activity. Kriging (KR), also called Gaussian Process, is considered one of the most precise regression or classification model, yet also very expensive in terms of computation costs related to training. Large precision or large data set sizes increase training times even more in an exponential scale, rendering many AI and Machine Learning projects with a low performance or even unfeasible.
VMC Consulting offers a new algorithm called Fast Kriging (FKR), also called Tessellated Partitions Surface with Kriging (TPS-KR), which allows to train KR with large data sets at a speed hundreds of times faster, without compromising precision.
Advantages of FKR
- Fast training times, 100+ times faster
- Same precision of KR
- Can be applied to regression or classification models
Bring the efficiency of leading-edge algorithms to your Machine Learning and AI projects, at www.vmc-consulting.net.