The distribution of these different numbers in the data determine the entropy. The level of randomness in the data is very high. You don’t know what you are going to get.
When you get a number, you might get number 4, or you might get number 7, or any other number.
If these 100 numbers contain different numbers, then the data is in a disorder state. If we have 100 numbers and all of them is 5, then the data is in very good order. Similary in data analytics, entropy is the level of disorder or randomness in the data. In thermodynamics, Entropy is the level of disorder or randomness in the system. Entropy is the level of disorder in the data. In this article I would like to focus on Entropy and Information Gain, using investment funds as an example. Classification is when the output is a category. Regression is when the output is a number. It can be used for both regression and classification.
Then we can use it to predict the output. So we train the model using a dataset, in order for it to learn. We can understand how it works.ĭecision Tree is a supervised machine learning algorithm. But the main reason it is widely used is the interpretability. It is relatively simple, yet able to produce good accuracy. Decision Tree is one of the most popular algorithms in machine learning.
