IForestASD with pysad

iforestasd.py

import numpy as np
from sklearn.utils import shuffle
from pysad.models import IForestASD
from pysad.transform.preprocessing import InstanceUnitNormScaler
from pysad.transform.postprocessing import RunningAveragePostprocessor
from pysad.utils import Data
from pysad.evaluation import AUROCMetric
from pysad.utils.array_streamer import ArrayStreamer
from tqdm import tqdm
import pandas as pd

if __name__ == "__main__":
    np.random.seed(61)  # Fix random seed.

    # Load data from CSV using pandas
    df = pd.read_csv('data/fraudTrain.csv')

    # Assuming the 'is_fraud' column contains the labels (1 for fraud, 0 for normal)
    labels = df['is_fraud']
    
    # Drop non-numeric columns and the label column
    features = df.drop(['trans_date_trans_time', 'merchant', 'category', 'first', 'last', 'gender', 
                        'street', 'city', 'state', 'job', 'dob', 'trans_num', 'is_fraud'], axis=1)

    # Shuffle the data
    features, labels = shuffle(features, labels)

    iterator = ArrayStreamer(shuffle=False)  # Init streamer to simulate streaming data.

    model = IForestASD()  # Init xStream anomaly detection model.
    preprocessor = InstanceUnitNormScaler()  # Init normalizer.
    postprocessor = RunningAveragePostprocessor(window_size=5)  # Init running average postprocessor.
    auroc = AUROCMetric()  # Init area under the receiver-operating characteristics curve metric.

    for X, y in tqdm(iterator.iter(features.values[100:1000], labels.values[100:1000])):  # Stream data.
        # Assuming X is 1-dimensional
        X_numeric = preprocessor.fit_transform_partial(X[[5, 6, 7, 9]])
        X[[5, 6, 7, 9]] = X_numeric  # Replace the transformed elements back into the original array
        
        score = model.fit_score_partial(X)  # Fit model to and score the instance.
        score = postprocessor.fit_transform_partial(score)  # Apply running averaging to the score.

        auroc.update(y, score)  # Update AUROC metric.

    # Output resulting AUROCS metric.
    print("AUROC: ", auroc.get())