model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
import numpy as np from sklearn.preprocessing import StandardScaler from tensorflow.keras.models import Sequential from tensorflow.keras.layers import Dense SCS2 Cheat Semi-External For CS2 BEST
# Labeling data X = np.concatenate((normal_data, cheating_data)) y = np.array([0]*len(normal_data) + [1]*len(cheating_data)) 10)) cheating_data = np.random.normal(5
# Simulated dataset of normal and cheating behaviors normal_data = np.random.normal(0, 1, size=(1000, 10)) cheating_data = np.random.normal(5, 1, size=(100, 10)) SCS2 Cheat Semi-External For CS2 BEST
scaler = StandardScaler() X_scaled = scaler.fit_transform(X)