NEW
Font size
WorksheetsEAE_DataScience_S2
Total questions: 10
Worksheet time: 5mins
Which is the most typical error when integration data from different sources?
Merge records that are different
Create new data
Keep duplicated records
Remove outliers
Which is the most used visualization techniques when performing exploratory analysis?
Scatterplots
Historgrams
Box Plots
All previous ones
What type of correlation can be seen in the following scatterplot?
No correlation
Perfect positive correlation
Perfect negative correlation
Strong negative correlation
Which step is typical from a Data cleaning phase?
Feature engineering
Outliers analysis
Discretization
Dimensionality reduction
What type of atribute can contain the following values?
Numerical
Ordinal
Nominal
None of the previous ones
Which of the following items is not a method to deal with missing values?
Predict a value
Filter an instance
PCA
Discretize
What is the problem that can arise if you want to take into account all possible features?
The curse of dimensionality
Not achieving a convergence
Creating redundant data
Losing data
Principal Component Analysis is a supervised Algorithm
True
False
If we create an attribute called "Age at the time of purchase", what are we doing?
Feature reduction
Discretization
Feature Engineering
Convert to categorical
What are we probably doing when we create a “1 to n-1” flag?
Quantization
Discretization
Convert a categorical attribute into numerical
Convert and ordinal attribute to numerical
