These machine learning algorithms are must to explore

In a world where all the manual tasks are automated, machine learning algorithms can help computers in playing chess, get smarter and to perform surgeries. One of the vital features of this revolution is how computing tools and techniques have been democratized. Machine learning can be supervised, unsupervised, semi-supervised and reinforcement learning. If you are one of the data scientists or machine learning enthusiasts then you should get a hang of the machine learning algorithms. Here are the top 10 latest machine learning algorithms to explore in 2022.

1 Linear Regression

In the linear regression process, the relationship is established between independent and dependent variables by fitting them to a line. This line is termed a regression line and is represented by a linear equation Y=a*X+b. The coefficients a & b are derived by minimizing the sum of the squared difference of distance between data points and the regression line. This is one of the machine learning algorithms to be explored for sure in 2022.

2 Logistic Regression

Logistic Regression is used to estimate discrete values from a set of independent variables. It helps in anticipating the probability of an event by fitting data to a logit function. It is also called logit regression. The methods such as interaction terms, eliminate features, regularize techniques and use a non-linear model that can help in improving logistic regression models.

3 Decision Tree

Decision tree in machine learning algorithms which is one of the widely popular in today's use. It is a supervised learning algorithm that is used for classifying problems. It works well with both continuous and categorical dependent variables. In this particular machine learning algorithm, we split the popular into two or more homogenous sets based on the most vital attributes. This is one of the machine learning algorithms to be explored for sure in 2022.

4 SVM

SVM is one of the machine learning algorithms that is used to classify algorithms in which you plot raw data as points in an n-dimensional space. In this algorithm, we split the population into two or more homogeneous sets based on the most significant attributes of independent variables.

5 Naive Bayes Algorithm

Naive Bayes classifier assumes that the presence of a particular feature in a class is unrelated to the presence of any other feature. Even if these features are related to each other, a Naive Bayes classifier would consider all of these properties independently when calculating the probability of a particular outcome. A Naive Bayesian model is easy to build and useful for massive datasets. This is one of the machine learning algorithms to be explored for sure in 2022. It's simple and is known to outperform even highly sophisticated classification methods.

6 KNN

These algorithms can be applied to both regression problems and classification.  This is one of the machine learning algorithms that is widely used to solve classification problems. KNN can be easily understood by comparing even our real life. But the only issue with KNN is that it is expensive and that still needs to be pre-processed.

7 K-Means

It is an unsupervised learning algorithm that solves clustering problems. And data is classified into a particular number of clusters in such a way that data points within a cluster are homogenous and heterogenous from data in other clusters too. This is one of the ML algorithms to be explored for sure in 2022.

8 Random Forest Algorithm

A collective of decision trees is called a random forest and it is used to classify a new object based on its attributes; each tree is classified and the tree votes for that class. The forest chooses the classification having the most votes (over all the trees in the forest).

9 Dimensionality Reduction Algorithms

In today's world, vast amounts of data are being stored and analyzed by corporations, government agencies, and research organizations. As a data scientist, you know that this raw data contains a lot of information – the challenge is in identifying significant patterns and variables. Dimensionality reduction algorithms like decision tree, factor analysis, missing value ratio and random forest can help you find relevant details. This is one of the machine learning algorithms to be explored for sure in 2022.

10. Gradient Boosting Algorithm and Ada Boosting Algorithm

These are boosting algorithms used when massive loads of data have to be handled to make predictions with high accuracy. Boosting is an ensemble learning algorithm that combines the predictive power of several base estimators to improve robustness. This is one of the ML algorithms to be explored for sure in 2022.