Types of Machine Learning Algorithms
In a world saturated by artificial intelligence, machine learning, and over-zealous talks about both, it is important to understand and identify the types of machine learning we may encounter. For the practitioners creating these algorithms, it’s essential to know the types of machine learning so that for any given task they may encounter, they can craft the proper learning environment and understand what to apply.
Machine Learning can be broadly classified into 3 types :- Supervised learning, Unsupervised learning and Reinforcement Learning.
Supervised learning is the most popular paradigm for machine learning. It is the easiest to understand and the simplest to implement. Supervised machine learning algorithms are designed to learn by example. The name “supervised” learning originates from the idea that training this type of algorithm is like having a teacher supervise the whole process.
When training a supervised learning algorithm, the training data will consist of inputs paired with the correct outputs. During training, the algorithm will search for patterns in the data that correlate with the desired outputs. After training, a supervised learning algorithm will take in new unseen inputs and will determine which label the new inputs will be classified as based on prior training data. The objective of a supervised learning model is to predict the correct label for newly presented input data. At its most basic form, a supervised learning algorithm can be written simply as:
Where Y is the predicted output that is determined by a mapping function that assigns a class to an input value x. The function used to connect input features to a predicted output is created by the machine learning model during training.
Supervised learning can be split into two subcategories: Classification and Regression.
Some examples of Classification are Identity fraud detection, Spam E-mail detection, Image Classification etc. Population growth prediction, Market Forecasting, Weather Forecasting etc. are some common examples of Regression.
