Model Description:

Regression is a supervised machine learning method for understanding the relationship between independent variables or features and a dependent variable or outcome. One of the algorithms used for regression is the “Ridge Regression”.
Here, we use the earthquake.csv dataset for regression purposes and you can download the dataset from the link on top of this page. This dataset has 3 features:
“Latitude”, “Longitude” and “Depth”
And the prediction variable is: “Earthquake Magnitude”.
In the above form, you enter the values of 3 features and the model returns the Earthquake Magnitude in a pop-up form. Notice that the values and ranges of each feature are as below:

-11 < Latitude < 6

95 < Longitude < 141

1 < Depth < 750

The sample code used to train a “Ridge Regression” model, is provided in the link on top of this page. Each time you run this form and predictions happen, the values will store in the database, and with the link “result” on top of this page, you will see the previous results of the model prediction. Your recent run will be added to the end of this list.