Hello everyone. In this video we will be discussing the types of Algorithm in machine learning. There are many Algorithms in machine learning and many more are yet being developed.
But all of the machine learning Algorithm can be classified into three main categories. And they are
- Supervised learning Algorithm
- Unsupervised learning Algorithm
- Reinforcement learning Algorithm
1. Supervised learning Algorithm
supervised learning Algorithm are used when the given data has both independent variables and the target variable. And the task of the supervised learning algorithm is to find the relationship between independent variables and the target variable.
And supervised learning Again there are two categories
- Algorithm for regression type problems – When the target variable has continuous values, regression type Algorithms can be used.
2. Algorithm for classification type problems – when the target variables have discrete or fixed set of values, we can use classification type Algorithm.
Some of the popular supervised learning Algorithm are linear regression,
- Logistic regression
- L nearest neighbors
- Support vector machines
- Decision trees
- Random forests
- Naive Bayes
2. unsupervised learning Algorithm
Unsupervised learning Algorithms can be used when there are no target variables. In this case, we are not trying to predict anything, we are just trying to find the pattern in the data if there is any.
Some of the popular unsupervised learning Algorithm are
- k means clustering
- Hierarchical clustering
- Single linkage clustering
3. Reinforcement learning Algorithm
Reinforcement Learning is all about letting an agent to interact in an environment. The agent will be rewarded for doing positive work and punished for doing negative work in the environment.
Let’s assume you are training your dog to do certain trick. Whenever your dog does the trick right, you will reward it by giving some treat.
If the dog does the trick wrong, you will simply punish it by not giving any treat, the dog will understand this and trust To perform the trick correctly so as to maximize the positive reward.