Machine Learning Random Forest with Python from Scratch - Categorical to Numeric Conversion

Machine Learning Random Forest with Python from Scratch - Categorical to Numeric Conversion

Assessment

Interactive Video

•

Information Technology (IT), Architecture, Mathematics

•

University

•

Practice Problem

•

Hard

Created by

Wayground Content

FREE Resource

The video tutorial covers the conversion of categorical variables to numerical values, essential for machine learning models. It explains the importance of data cleaning, including removing outliers, handling missing values, and converting categorical data. The tutorial demonstrates using Pandas to perform these tasks, focusing on the Titanic data set. It concludes with preparing a clean data set ready for machine learning algorithms, specifically random forest implementation.

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10 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Why is it necessary to convert categorical variables to numerical values in machine learning?

It improves the accuracy of the model.

It reduces the size of the dataset.

It makes the data more readable.

Machines can only process numerical data.

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

In the gender conversion example, what numerical value is assigned to 'male'?

2

1

0

3

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What method in pandas is used to convert categorical variables into dummy/indicator variables?

pd.to_category()

pd.to_numeric()

pd.get_dummies()

pd.convert()

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the purpose of adding a prefix when creating dummy variables?

To increase the size of the dataset.

To sort the columns alphabetically.

To indicate the original variable the dummy was created from.

To make the column names shorter.

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which columns are typically removed after creating dummy variables?

Columns with unique identifiers.

Columns with numerical data.

Columns with missing values.

Original categorical columns.

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Why is the 'Passenger ID' column considered unnecessary for the model?

It contains duplicate values.

It is too large.

It does not contribute to predicting survival.

It is a categorical variable.

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the final step in preparing the dataset for machine learning?

Adding more columns.

Removing all numerical columns.

Saving the cleaned dataset.

Converting all data to text.

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