I try to detect anomaly data from dataframe (dataset).
I used OneClassSVM and split train and test data (20% for test) and detect anomaly data, but at last I want one column with all data for each row with 0 or 1 for output(not just for test data).
Now OneClassSVM predict for test data and:
#Predic The Anomalies
prediction = One_Class_Svm.predict(X_test)
#change the anomalies value to make consistent with the True value
prediction = [1 if i == -1 else 0 for i in prediction]
I have main output for prediction and should compare this column with prediction (for all data).
For example: for 12000 samples after predict and detect anomaly I have one column((2400 * 1)shape, for y_test prediction).
And 9600 samples were for train.
At last I want to have one column that have 12000*1 dimension to compare prediction with main output.