A decision tree is a mechanical way to make a decision by dividing the inputs into smaller decisions. Like other models, it involves mathematics. But it’s not very complicated mathematics. We look at a g...

is similar to the decision tree, except the questions that are posed include some randomness. The goal is to push out bias and group outcomes based upon the most likely positive responses. These collecti...

It is based on the concept of dependent probability. If you roll a dice, the probability of getting a 6 is 1/6 since there are 6 sides. What is the probability that you get a 5 after rolling a 6? It’s no...

Categorization or grouping of machine learning algorithms is done in many ways i.e. Classification, Regression, Supervised, Un-Supervised, Probabilistic and Non-Probabilistic and many more. There are sev...

Categorizing data points based on their distance to other points in a training data set can be a simple yet effective way of classifying data. k-nearest neighbor (KNN) is the “guilty by association” algo...

It is important to ensure that the machine learning algorithm of choice is effective across several inputs. This means that the machine learning algorithm of choice does not face degradation on the new i...