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What Are The Machine Learning Algorithms?


What Are The Machine Learning Algorithms?

A machine learning algorithm is the method by which the AI system conducts its task, generally predicting output values from given input data. The two main processes of machine learning algorithms are classification and regression. Machine learning algorithms are programs that adjust themselves to perform better as they are exposed to more data. The “learning” part of machine learning means that those programs change how they process data over time, much as humans change how they process data by learning.

So a machine learning algorithm is a program with a specific way to adjusting its own parameters, given feedback on its previous performance in making predictions about a dataset.

There is a wide variety of machine learning algorithms that can be grouped in three main categories: Supervised learning algorithms model the relationship between features (independent variables) and a label (target) given a set of observations. Then the model is used to predict the label of new observations using the features. Depending on the characteristics of target variable, it can be a classification (discrete target variable) or a regression (continuous target variable) task.

Unsupervised learning algorithms try to find the structure in unlabeled data. Reinforcement learning works based on an action-reward principle. An agent learns to reach a goal by iteratively calculating the reward of its actions.

Top 10 Machine Learning Algorithms 2022

  1. 1 . Linear Regression
  2. 2 .Logistic Regression
  3. 3 .CART
  4. 4 .Naïve Bayes
  5. 5 .KNN
  6. 6 .Apriori
  7. 7. K-means
  8. 8 .PCA
  9. 9 .Bagging with Random Forests
  10. 10 .Boosting with AdaBoost