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Lære Challenge: Rule-based Approach | 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: Rule-based Approach

Oppgave

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Your task is to create a function that identifies outliers based on the Euclidean distance between each data point and the mean value of the dataset:

  1. Calculate the Euclidean distance for each data point in the dataset.
  2. If the calculated distance of a data point falls outside a predefined range, classify it as an outlier.
  3. Create a list to store the identified outliers and print the list.

Once you've completed this task, click the button below the code to check your solution.

Løsning

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Takk for tilbakemeldingene dine!

Seksjon 2. Kapittel 2
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book
Challenge: Rule-based Approach

Oppgave

Swipe to start coding

Your task is to create a function that identifies outliers based on the Euclidean distance between each data point and the mean value of the dataset:

  1. Calculate the Euclidean distance for each data point in the dataset.
  2. If the calculated distance of a data point falls outside a predefined range, classify it as an outlier.
  3. Create a list to store the identified outliers and print the list.

Once you've completed this task, click the button below the code to check your solution.

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 2
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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