Is a zip code a discrete variable?

continuous Discrete Attribute Has only a finite or countably infinite set of values Examples from text: zip codes, counts, or the set of words in a collection of documents, binary data.

Is zip code a nominal variable?

Nominal variables are also called categorical variables or factors. Nominal variables may be represented by numbers. If so, these numbers are used merely as labels and are not subjected to arithmetic operations. “Zip Code” is a nominal variable whose values are represented by numbers.

Do zip codes increase from east to west?

Yes, since ZIP codes increase from east to west.

How do you handle categorical data with high cardinality?

How handle high cardinality

1. Label Encoder : Replace string values by integer classes [0, 1, 2, 3…]
2. Dummy Encoder : This method consist on creating n new variables of.
3. Aggregating Values : This method consist on aggregating values with low cardinality by creating a “Others” class.

What happens when you apply very large penalty in case of Lasso?

16) What will happen when you apply very large penalty? In lasso some of the coefficient value become zero, but in case of Ridge, the coefficients become close to zero but not zero.

What does large values of the log likelihood statistic indicate?

Large values of the log-likelihood statistic indicate: That there are a greater number of explained vs. unexplained observations. That the statistical model fits the data well.

Which of the following is one of the largest boost subclass in boosting?

Explanation: mboost is used for model based boosting. 9. Which of the following is one of the largest boost subclass in boosting? Explanation: R has multiple boosting libraries.

Which of the following algorithm do we use for variable selection?

9) Which of the following algorithms do we use for Variable Selection? In case of lasso we apply a absolute penality, after increasing the penality in lasso some of the coefficient of variables may become zero.

What is discrete random variable give an example?

Example (Discrete Random Variable) Flipping a coin twice, the random variable Number of Heads 2f0;1;2gis a discrete random variable. Number of aws found on a randomly chosen part 2f0;1;2;:::g.

When should I standardize the independent variables in regression analysis?

In regression analysis, you need to standardize the independent variables when your model contains polynomial terms to model curvatureor interaction terms. These terms provide crucial information about the relationships between the independent variables and the dependent variable, but they also generate high amounts of multicollinearity.

How to use the regression command to code categorical data?

From this point we will refer to a coding scheme when used with the regression command as regression coding. Another method for analyzing categorical data would be to use the glm command and then you could use the / lmatrix or the / contrast subcommands to perform comparisons among the levels of the categorical variable.

How to interpret interaction values in a regression model?

Interpret these values in the usual manner. Standardizing the independent variables produces vital benefits when your regression model includes interaction terms and polynomial terms. Always standardize your variables when the model has these terms. Keep in mind that it is enough to center the variables for a more straightforward interpretation.