Which regions will present higher business opportunities for the growth of the Tableau services market in the future?

The Asia Pacific will present more business opportunities to facilitate market growth. The region features constant development in the business infrastructure of companies. Also, in this region, there is quick digitalization at workplaces.

Why is logistic regression called regression instead of classification?

The primary difference between regression and classification is the output variable in the regression is continuous whereas, in classification, it is discrete. Logistic regression is a supervised classification algorithm. Its model creates a regression model similar to linear regression to forecast the likelihood for a specific data entry belonging to the category labeled as ‘1’.

What is the significance of regularized logistic regression?

Regularisation in logistic regression is a method capable of solving the issue of overfitting a model. This technique is advantageous when a huge number of parameters exist and these parameters help forecast the target function. In these cases, it is challenging to set features for manual operation and features for automatic operation. Hence, the regularized logistic regression helps you determine pertinent parameters and solve the overfitting issue.

Which is the most popular algorithm for variable selection?

Lasso is the most popular algorithm for variable selection. The reason is it carries out logistic regression analysis with the help of a shrinkage parameter resulting in data shrinking to a point. The variable selection takes place by pushing the value of coefficients of less significant variables to 0 via a penalty.

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