Quantum Regression
==================

This tutorial demonstrates regression with ``VQCRegressor``.

Setup
------

.. code-block:: python

   import numpy as np
   from sklearn.model_selection import train_test_split
   from sklearn.metrics import mean_squared_error
   from psipose.estimators import VQCRegressor

Generate Data
-------------

.. code-block:: python

   np.random.seed(42)
   X = np.sort(5 * np.random.rand(100, 1), axis=0)
   y = np.sin(X).ravel() + np.random.normal(0, 0.1, X.shape[0])
   X_train, X_test, y_train, y_test = train_test_split(
       X, y, test_size=0.3, random_state=42
   )

Train Regressor
----------------

.. code-block:: python

   reg = VQCRegressor(n_qubits=3, n_iter=100, random_state=42)
   reg.fit(X_train, y_train)

Evaluate
---------

.. code-block:: python

   y_pred = reg.predict(X_test)
   mse = mean_squared_error(y_test, y_pred)
   print(f"MSE: {mse:.4f}")