What are the feature selection methods?

There are two main types of feature selection techniques: supervised and unsupervised, and supervised methods may be divided into wrapper, filter and intrinsic.

What do you do with categorical features?

One-Hot Encoding is the most common, correct way to deal with non-ordinal categorical data. It consists of creating an additional feature for each group of the categorical feature and mark each observation belonging (Value=1) or not (Value=0) to that group.

What are the types of categorical data?

There are two types of categorical data, namely; the nominal and ordinal data.

• Nominal Data. This is a type of data used to name variables without providing any numerical value.
• Ordinal Data. This is a data type with a set order or scale to it.

How are categorical variables used in classification?

Improve classification with many categorical variables

1. For each categorical variable with many possible value, take only the one having more than 10000 sample that takes this value.
2. Build dummy variable for each categorical one (if 10 countries then for each sample add a binary vector of size 10).

What is feature subset selection in data mining?

Feature Selection methods in Data Mining and Data Analysis problems aim at selecting a subset of the variables, or features, that describe the data in order to obtain a more essential and compact representation of the available information.

What do you mean by feature selection?

Feature Selection is the process where you automatically or manually select those features which contribute most to your prediction variable or output in which you are interested in. Having irrelevant features in your data can decrease the accuracy of the models and make your model learn based on irrelevant features.

Which of the following is a categorical feature?

Answer: Branch of an engineering student. Explanation: Branch of an engineering student Is a categorical feature.