Machine Learning Random Forest with Python from Scratch - Outliers Removal

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Information Technology (IT), Architecture, Social Studies
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University
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Hard
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7 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is an outlier in a dataset?
A data point that is the average of all other data points
A data point that is missing from the dataset
A data point that is exactly the same as other data points
A data point that is significantly different from other data points
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Why is manually identifying outliers considered inefficient?
It requires specialized software
It is time-consuming and impractical for large datasets
It can only be done by data scientists
It is not accurate
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which tool is mentioned as useful for visualizing data to detect outliers?
Tableau
Power BI
Excel
Matplotlib
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What type of graph is used to visualize the distribution of ages in the dataset?
Line graph
Bar chart
Histogram
Pie chart
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the criterion used to remove outliers from the dataset in this tutorial?
Age equal to 100
Age less than 100
Age greater than 100
Age not equal to 100
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
After removing outliers, what is the next step mentioned in the data cleaning process?
Converting categorical data to numeric data
Converting numeric data to categorical data
Adding more outliers
Deleting the dataset
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the purpose of saving the dataset after removing outliers?
To ensure data is backed up
To prepare for further analysis
To delete unnecessary data
To share with other team members
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