## How does regression algorithm work?

Simple linear regression is a type of regression analysis where the number of independent variables is one and there is a linear relationship between the independent(x) and dependent(y) variable.

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The motive of the linear regression algorithm is to find the best values for a_0 and a_1..

## Which regression algorithm predicts continuous values?

1. Simple Linear Regression model: Simple linear regression is a statistical method that enables users to summarise and study relationships between two continuous (quantitative) variables.

## Which algorithm is used for prediction?

Naive Bayes is a simple but surprisingly powerful algorithm for predictive modeling. The model is comprised of two types of probabilities that can be calculated directly from your training data: 1) The probability of each class; and 2) The conditional probability for each class given each x value.

## Which machine learning algorithm is more applicable for continuous data?

Decision treeAnswer. Explanation: Decision tree is more applicable for continuous data .

## How do you call the process of predicting a continuous value?

Regression is the task of predicting a continuous quantity.

## Which regression model is best?

Statistical Methods for Finding the Best Regression ModelAdjusted R-squared and Predicted R-squared: Generally, you choose the models that have higher adjusted and predicted R-squared values. … P-values for the predictors: In regression, low p-values indicate terms that are statistically significant.More items…•