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.
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…•