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Lære Challenge: Outlier Detection Using MAD Rule | Statistical Methods in Anomaly Detection
Data Anomaly Detection
course content

Kursusindhold

Data Anomaly Detection

Data Anomaly Detection

1. What is Anomaly Detection?
2. Statistical Methods in Anomaly Detection
3. Machine Learning Techniques

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Challenge: Outlier Detection Using MAD Rule

Opgave

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Now, you will use the MAD rule to detect outliers in the California Housing Dataset. It contains various features related to housing characteristics in different districts in California.

In this task, we will detect outliers in the column MedInc, which stands for Median Income.

Your task is to:

  1. Fill in all gaps in mad() function to calculate Mean Absolute Deviation.
  2. Calculate the threshold using value 3 as a threshold value.
  3. Specify the rule to detect outliers that will be stored in the outliers variable.

Løsning

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Var alt klart?

Hvordan kan vi forbedre det?

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Sektion 2. Kapitel 6
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book
Challenge: Outlier Detection Using MAD Rule

Opgave

Swipe to start coding

Now, you will use the MAD rule to detect outliers in the California Housing Dataset. It contains various features related to housing characteristics in different districts in California.

In this task, we will detect outliers in the column MedInc, which stands for Median Income.

Your task is to:

  1. Fill in all gaps in mad() function to calculate Mean Absolute Deviation.
  2. Calculate the threshold using value 3 as a threshold value.
  3. Specify the rule to detect outliers that will be stored in the outliers variable.

Løsning

Switch to desktopSkift til skrivebord for at øve i den virkelige verdenFortsæt der, hvor du er, med en af nedenstående muligheder
Var alt klart?

Hvordan kan vi forbedre det?

Tak for dine kommentarer!

Sektion 2. Kapitel 6
Switch to desktopSkift til skrivebord for at øve i den virkelige verdenFortsæt der, hvor du er, med en af nedenstående muligheder
Vi beklager, at noget gik galt. Hvad skete der?
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