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.
This exercise is part of the course
Anomaly Detection in Python
Exercise instructions
- Import the
KNN
estimator from the relevantpyod
module. - Instantiate a
KNN()
estimator with 0.5% contamination and 20 neighbors asknn
. - Create a boolean index named
is_outlier
that returnsTrue
when thelabels_
ofknn
return 1. - Isolate the outliers from
females
usingis_outlier
intooutliers
.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# 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))