You need to predict the sea level in meters for the next 10 years.
Which type of machine learning should you use?
Click on the arrows to vote for the correct answer
A. B. C.B
In the most basic sense, regression refers to prediction of a numeric target.
Linear regression attempts to establish a linear relationship between one or more independent variables and a numeric outcome, or dependent variable.
You use this module to define a linear regression method, and then train a model using a labeled dataset. The trained model can then be used to make predictions.
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/linear-regressionThe type of machine learning algorithm that should be used for predicting the sea level in meters for the next 10 years is regression.
Regression is a type of supervised learning algorithm that is used for predicting a continuous output value based on input features. In this case, the input features would be time-based data on sea level, and the output value would be the predicted sea level for the next 10 years.
Regression algorithms use statistical methods to model the relationship between input features and output values. They can take into account factors such as time trends, seasonal variations, and other patterns in the data to make accurate predictions.
On the other hand, classification is a type of supervised learning algorithm that is used for predicting a categorical output value, such as whether an email is spam or not. In this case, predicting the sea level in meters is not a categorical variable, but a continuous one.
Clustering, on the other hand, is an unsupervised learning algorithm that is used for grouping similar data points together based on their features. It is not suitable for predicting sea level values over time.
Therefore, the correct answer is B. regression.