KNN for the first time

You will practice KNN for the first time on a version of the Ansur Body Measurements dataset for females. The female version also contains 95 columns but only 1.9k observations.

The dataset has been loaded as females into the environment.

Deze oefening maakt deel uit van de cursus

Anomaly Detection in Python

Bekijk cursus

Oefeninstructies

Import the KNN estimator from the relevant pyod module.
Instantiate a KNN() estimator with 0.5% contamination and 20 neighbors as knn.
Create a boolean index named is_outlier that returns True when the labels_ of knn return 1.
Isolate the outliers from females using is_outlier into outliers.

Interactieve oefening met praktijkervaring

Probeer deze oefening door deze voorbeeldcode aan te vullen.

# Import KNN from the relevant pyod module
from pyod.____ import ____

# Instantiate KNN and fit to females
knn = KNN(____, ____, n_jobs=-1)
knn.____

# Create a boolean index that checks for outliers
is_outlier = ____

# Isolate the outliers
outliers = ____

print(len(outliers))

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