import pandas as pd
import numpy as np
iris = pd.read_csv("../data/iris.csv")
print(iris)
xx = iris[["sepal_length","sepal_width","petal_length","petal_width"]]
print(xx)
from sklearn.ensemble import IsolationForest
isf = IsolationForest()
train = isf.fit(xx)
predik = isf.predict(xx)
print(predik)
df_pre = pd.DataFrame(predik)
print(df_pre)
print(df_pre.value_counts())Output
/home/mfahri/OneDrive/ml/venv/bin/python /home/mfahri/OneDrive/ml/belajar/iris_eda.py
sepal_length sepal_width petal_length petal_width species
0 5.1 3.5 1.4 0.2 setosa
1 4.9 3.0 1.4 0.2 setosa
2 4.7 3.2 1.3 0.2 setosa
3 4.6 3.1 1.5 0.2 setosa
4 5.0 3.6 1.4 0.2 setosa
.. ... ... ... ... ...
145 6.7 3.0 5.2 2.3 virginica
146 6.3 2.5 5.0 1.9 virginica
147 6.5 3.0 5.2 2.0 virginica
148 6.2 3.4 5.4 2.3 virginica
149 5.9 3.0 5.1 1.8 virginica
[150 rows x 5 columns]
sepal_length sepal_width petal_length petal_width
0 5.1 3.5 1.4 0.2
1 4.9 3.0 1.4 0.2
2 4.7 3.2 1.3 0.2
3 4.6 3.1 1.5 0.2
4 5.0 3.6 1.4 0.2
.. ... ... ... ...
145 6.7 3.0 5.2 2.3
146 6.3 2.5 5.0 1.9
147 6.5 3.0 5.2 2.0
148 6.2 3.4 5.4 2.3
149 5.9 3.0 5.1 1.8
[150 rows x 4 columns]
[ 1 1 1 1 1 -1 1 1 -1 1 1 1 1 -1 -1 -1 -1 1 -1 1 1 1 -1 -1
1 1 1 1 1 1 1 1 -1 -1 1 1 1 1 1 1 1 -1 1 -1 -1 1 1 1
1 1 -1 1 1 1 1 1 1 -1 1 1 -1 1 -1 1 1 1 1 1 -1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 -1 1 1
1 1 -1 1 -1 1 1 1 1 -1 -1 -1 -1 -1 1 1 1 -1 -1 1 1 -1 -1 -1
1 1 -1 1 1 1 1 1 1 -1 -1 -1 1 1 1 -1 -1 1 1 1 1 1 1 1
-1 1 1 1 -1 1]
0
0 1
1 1
2 1
3 1
4 1
.. ..
145 1
146 1
147 1
148 -1
149 1
[150 rows x 1 columns]
1 110
-1 40
dtype: int64
Process finished with exit code 0
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