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QuantumKernelTrainer qkt = QuantumKernelTrainer( quantum_kernel=quant_kernel, loss="svc_loss", optimizer=spsa_opt, initial_point=[np.pi / 2] ) # Reduce dimensionality of the data using PCA from sklearn.decomposition import PCA pca = PCA(n_components=2) X_ = pca.fit_transform(X) # Train the quantum