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

Kursinnhold

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

Oppgave

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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

Switch to desktopBytt til skrivebordet for virkelighetspraksisFortsett der du er med et av alternativene nedenfor
Alt var klart?

Hvordan kan vi forbedre det?

Takk for tilbakemeldingene dine!

Seksjon 2. Kapittel 6
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book
Challenge: Outlier Detection Using MAD Rule

Oppgave

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 desktopBytt til skrivebordet for virkelighetspraksisFortsett der du er med et av alternativene nedenfor
Alt var klart?

Hvordan kan vi forbedre det?

Takk for tilbakemeldingene dine!

Seksjon 2. Kapittel 6
Switch to desktopBytt til skrivebordet for virkelighetspraksisFortsett der du er med et av alternativene nedenfor
Vi beklager at noe gikk galt. Hva skjedde?
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