Top Trending Machine Learning Algorithms in 2022
To gain more powerful and accurate results instantly
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Machine learning is a trending topic over the past few years. It is still trending in 2022. Although there are many machine learning algorithms in use, we often prefer to use some specific set of algorithms. A great example of that is the Kaggle grand prize winners have often used the same specific set of algorithms.
The main factor behind top trending machine learning algorithms is that they are more powerful and provide accurate results instantly.
From my experience, I’ve carefully chosen some of the top trending machine learning algorithms that are worth studying in 2022.
Let’s discuss them in detail.
1. XGBoost
This is my number one choice and definitely the same among Kaggle grand prize winners. XGBoost is a tree-based algorithm that consists of an ensemble (group) of boosted trees. In XGBoost, new trees are created by correcting the errors of previous trees. This technique is known as boosting. Therefore, XGBoost is one of the boosting algorithms.
Reasons for the choice
- XGBoost can outperform almost any machine learning algorithm. So, we can use it to gain more powerful and accurate results.
- Its Scikit-learn compatible API is easy to use.
Category
- Supervised learning: Regression and Classification
My own resources
You can read my previously-published posts to learn more about XGBoost and its uses. You can also get coding experience by reading them.
- Setting up the coding environment for XGBoost
- Classification with XGBoost
- Regression with XGBoost
- Cross-validation with XGBoost
- Compare performance: XGBoost vs LightGBM
- Compare performance: XGBoost vs CatBoost
2. CatBoost
CatBoost is also a boosting algorithm and a great alternative to XGBoost. It has some unique features that other boosting algorithms don’t…
