Naive Bayes is a deceptively simple way to find answers to probability questions that involve many inputs. For example, if you're a website owner, you might be interested to know the probability that a visitor will make a purchase. That question has a lot of "what-ifs", including time on page, pages visited, and prior visits. Naive Bayes essentially allows you to take the raw inputs (i.e. historical data), sort the data into more meaningful chunks, and input them into a formula. …Continue
Added by Stephanie Glen on April 25, 2019 at 10:00am — No Comments
Bayesian Probability is like a reaction to the Mathematical Probability: what about our…Continue
Added by Marcia Ricci Pinheiro on February 16, 2019 at 11:30pm — No Comments
Bayesian Nonparametrics is a class of models with a potentially infinite number of parameters. High flexibility and expressive power of this approach enables better data modelling compared to parametric methods.
Bayesian Nonparametrics is used in problems where a dimension of interest grows with data, for example, in problems where the number of features is not fixed but allowed to vary as we observe more…Continue
Added by Luba Belokon on October 12, 2017 at 3:00pm — No Comments
High Performance Computing (HPC) plus data science allows public and private organizations get…Continue