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This article mainly introduces "what are the commonly used machine learning algorithms". In daily operation, I believe that many people have doubts about the commonly used machine learning algorithms. The editor consulted all kinds of materials and sorted out simple and easy-to-use operation methods. I hope it will be helpful for you to answer the doubts about "what are the commonly used machine learning algorithms?" Next, please follow the editor to study!

Supervised learning (Supervised Learning)

How it works: the algorithm consists of target / result variables (or dependent variables), which will be predicted from a given set of predictive variables (independent variables). Using these sets of variables, we generate a function that maps the input to the desired output. The training process continues until the model achieves the required accuracy in the training data. Examples of supervised learning: regression, decision tree, random forest, KNN,Logistic regression, etc.

Unsupervised learning (Unsupervised Learning)

How it works: in this algorithm, we do not have any goals or result variables to predict / estimate. It is used to cluster the population of different groups and is widely used to segment different groups of customers for specific intervention. Examples of unsupervised learning: Apriori algorithm, K-means.

Reinforcement learning (Reinforcement Learning)

How it works: using this algorithm, the machine can be trained to make specific decisions. It works in this way: the machine is exposed to an environment, and it constantly trains itself through trial and error. The machine learns from past experience and tries to capture the best possible knowledge to make accurate business decisions. An example of reinforcement learning: Markov decision-making process.

List of commonly used machine learning algorithms

Linear Regression (linear regression)

Logistic Regression (Logistic regression)

Decision Tree (decision tree)

SVM (support vector machine)

Naive Bayes (naive Bayes)

KNN (K-proximity algorithm)

K-Means (K-means algorithm)

Random Forest (random forest)

Dimensionality Reduction Algorithms (dimension reduction algorithm)

Gradient Boosting algorithms (gradient Boosting algorithm)

GBM

XGBoost

LightGBM

CatBoost

At this point, the study of "what are the commonly used machine learning algorithms" is over. I hope to be able to solve your doubts. The collocation of theory and practice can better help you learn, go and try it! If you want to continue to learn more related knowledge, please continue to follow the website, the editor will continue to work hard to bring you more practical articles!

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