Conteúdo do Curso
Data Anomaly Detection
Data Anomaly Detection
Challenge: Rule-based Approach
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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:
- Calculate the Euclidean distance for each data point in the dataset.
- If the calculated distance of a data point falls outside a predefined range, classify it as an outlier.
- 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.
Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixoObrigado pelo seu feedback!
Challenge: Rule-based Approach
Swipe to show code editor
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:
- Calculate the Euclidean distance for each data point in the dataset.
- If the calculated distance of a data point falls outside a predefined range, classify it as an outlier.
- 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.
Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixoObrigado pelo seu feedback!
Challenge: Rule-based Approach
Swipe to show code editor
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:
- Calculate the Euclidean distance for each data point in the dataset.
- If the calculated distance of a data point falls outside a predefined range, classify it as an outlier.
- 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.
Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixoObrigado pelo seu feedback!
Swipe to show code editor
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:
- Calculate the Euclidean distance for each data point in the dataset.
- If the calculated distance of a data point falls outside a predefined range, classify it as an outlier.
- 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.
Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixoMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo