Machine Learning Methods
Machine learning models can be categorized mainly into the following four types −
- Supervised Machine Learning
- Unsupervised Machine Learning
- Semi-supervised Machine Learning
- Reinforcement Machine Learning
Let's explore each of the above types of machine learning in detail.
Supervised Machine Learning¶
In supervised machine learning, the algorithm is trained on labeled data, meaning that the correct answer or output is provided for each input. The algorithm then uses this labeled data to make predictions about new, unseen data.
Unsupervised Machine Learning¶
In unsupervised machine learning, the algorithm is trained on unlabeled data, meaning that the correct output or answer is not provided for each input. Instead, the algorithm must identify patterns and structures in the data on its own.
Semi-supervised Machine Learning¶
Semi-supervised machine learning is a type of machine learning technique that is an integration of supervised and unsupervised learning as it uses a major portion of unlabeled dataset and minor portion of labeled data for training an algorithm preferably for classification and regression tasks.
Reinforcement Machine Learning¶
In reinforcement machine learning, the algorithm learns by receiving feedback in the form of rewards or punishments based on its actions. The algorithm then uses this feedback to adjust its behavior and improve performance.