Category: Decision Tree
1. Support-vector machine Given a set of training examples, each marked as belonging to one of two categories, an SVM training algorithm builds a model that assigns new examples to one category or the other, making it a non-probabilistic binary linear classifier (although methods such as Platt scaling exist to use SVM in a probabilistic […]
Analyzing Diabetes Patterns amongst Indians, A Beginner’s Guide to Pearson’s Correlation Coefficient, Deep Learning in Cyber Security & Much More!
1. Juicing out the Diabetes Patterns amongst Indians using Machine Learning The data indicates an increase of 266% in the population of diabetics is going to be witnessed by developing countries. The score of the training model was a magnificent 100% which means it classified all the elements correctly as is evident as a result […]
Introduction In this blog post, I am going to talk about a powerful supervised learning algorithm that is often used in Machine Learning competitions. It is called the Decision Tree algorithm. It can be used for both classification & regression tasks. In this post, I will discuss the need for tree-based algorithms, the basics of […]