import altair
from IPython.display import display
from sklearn.neighbors import LocalOutlierFactor
from sklearn.datasets import load_iris, load_linnerud
data = load_iris(as_frame=True).data
data["Outlier"] = LocalOutlierFactor(50).fit_predict(data) == -1
display(data[:3])
altair.Chart(data).mark_point().encode(
x="sepal length (cm)",
y="petal length (cm)",
color="Outlier"
)
sepal length (cm) | sepal width (cm) | petal length (cm) | petal width (cm) | Outlier | |
---|---|---|---|---|---|
0 | 5.1 | 3.5 | 1.4 | 0.2 | False |
1 | 4.9 | 3.0 | 1.4 | 0.2 | False |
2 | 4.7 | 3.2 | 1.3 | 0.2 | False |
data = load_linnerud(as_frame=True).data
data["Outlier"] = LocalOutlierFactor(10).fit_predict(data) == -1
display(data[:3])
altair.Chart(data).mark_point().encode(
x="Chins",
y="Jumps",
color="Outlier"
)
Chins | Situps | Jumps | Outlier | |
---|---|---|---|---|
0 | 5.0 | 162.0 | 60.0 | False |
1 | 2.0 | 110.0 | 60.0 | False |
2 | 12.0 | 101.0 | 101.0 | False |