where i am using label encoder to label the categorical column. However while transforming it back, i'm getting value error
I have used Label encoder from sklearn
Code:
from sklearn.preprocessing import LabelEncoder
enc = LabelEncoder()
label_encoder = enc.fit(Final.iloc[:,3])
print ("Categorical classes:", label_encoder.classes_)
integer_classes = label_encoder.transform(label_encoder.classes_)
print ("Integer classes:", integer_classes)
t = label_encoder.transform(Final.iloc[:,3])
Final.iloc[:, 3] = t
data = Final.iloc[:,3:11]
from sklearn.ensemble import IsolationForest
import numpy as np
clf=IsolationForest(n_estimators=100, max_samples='auto', contamination=float(.03))
clf.fit(data)
pred = clf.predict(data)
Final['anomaly']=pred
outliers=Final.loc[Final['anomaly']==-1]
outlier_index=list(outliers.index)
print(Final['anomaly'].value_counts())
t = label_encoder.inverse_transform(Final.iloc[:,3])
Final.iloc[:,3] = t
Error:
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()