Top 10 Machine Learning Algorithms
To state, one can not conclude that SVM is a better algorithm than decision trees or linear regression.
In this blog, we are going to look into the top machine learning algorithms.
A binomial logistical regression is restricted to 2 binary outputs and more than 2 classes can be achieved through a multinomial logistic regression.
Logistic regression is used to create an information category forecast for weighted entry scores by the logistic sigmoid function.
Multiple regression means an assessment of regression with two or more independent variables.
Logistic regression is traditionally a two-class classification problem algorithm.
K-NN is used in a range of machine learning tasks; k-NN, for example, can help in computer vision in hand-written letters and the algorithm is used to identify genes that are contributing to a specific characteristic of the gene expression analysis.
SVM. The support vector machine(SVM) is a supervised, classifying, and regressing machine learning algorithm.
Even an experienced data scientist cannot say which algorithm works best before distinct algorithms are tested.
While many other machine learning algorithms exist, they are the most common.