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- X_data = [X_data_distance]
- X_data = np.vstack(X_data).astype(np.float64)
- X_data = X_data.T
- y_data = X_data_orders
- #print(X_data.shape)
- #print(y_data.shape)
- #(10000, 1)
- #(10000,)
- X_train, X_test, y_train, y_test = train_test_split(X_data, y_data, test_size=0.33, random_state=42)
- svr_rbf = SVC(kernel= 'rbf', C= 1.0)
- svr_rbf.fit(X_train, y_train)
- plt.plot(X_data_distance, svr_rbf.predict(X_data), color= 'red', label= 'RBF model')
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