Quick Answer: What type of machine learning algorithm is suitable for predicting the continuous dependent variable?

Linear regression is used when the dependent variable is continuous and the nature of the regression line is linear. Logistic regression is used when the dependent variable is binary in nature.

What type of ML algorithm is suitable for predicting the continuous dependent variable?

Linear regression is to be used when the target variable is continuous and the dependent variable(s) is continuous or a mixture of continuous and categorical, and the relationship between the independent variable and dependent variables are linear.

Which machine learning algorithms is best for continuous data?

1) Linear Regression

It is one of the most-used regression algorithms in Machine Learning. A significant variable from the data set is chosen to predict the output variables (future values). Linear regression algorithm is used if the labels are continuous, like the number of flights daily from an airport, etc.

What type of machine learning algorithm is suitable for predicting the continuous dependent variable with two different values?

Linear regression is usually among the first few topics which people pick while learning predictive modeling. In this technique, the dependent variable is continuous, independent variable(s) can be continuous or discrete, and nature of regression line is linear.

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Which algorithm is best for regression problem?

Top 6 Regression Algorithms Used In Data Mining And Their Applications In Industry

  • Simple Linear Regression model.
  • Lasso Regression.
  • Logistic regression.
  • Support Vector Machines.
  • Multivariate Regression algorithm.
  • Multiple Regression Algorithm.

Which algorithm can be used for both continuous and binary dependent variables?

Regression models aim to project value based on independent features. The main difference that makes both different from each other is when the dependent variables are binary logistic regression is considered and when dependent variables are continuous then linear regression is used.

What is the easiest machine learning algorithm?

K-means clustering is one of the simplest and a very popular unsupervised machine learning algorithms.

Is regression an algorithm?

Linear regression

Linear Regression is an ML algorithm used for supervised learning. Linear regression performs the task to predict a dependent variable(target) based on the given independent variable(s).

Which of the following is regression based learning?

Summary. Regression is a supervised machine learning technique which is used to predict continuous values. The ultimate goal of the regression algorithm is to plot a best-fit line or a curve between the data. The three main metrics that are used for evaluating the trained regression model are variance, bias and error.

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