{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "0f20c1ae",
   "metadata": {},
   "source": [
    "# Day 3: Model Complexity and Generalization\n",
    "\n",
    "**Python + Machine Learning for Engineering Research**\n",
    "\n",
    "A useful umbrella phrase for today's ideas is **model complexity and generalization**. Instead\n",
    "of learning several new model families, we will ask deeper questions about models from yesterday:\n",
    "\n",
    "> When is a model too simple, too flexible, or too sensitive to its training data?\n",
    "\n",
    "### Today\n",
    "\n",
    "| Part | Topic |\n",
    "|---|---|\n",
    "| 0 | Review Assignment 2 |\n",
    "| 1 | Generalization: training performance is not the final goal |\n",
    "| 2 | Model complexity, underfitting, and overfitting |\n",
    "| 3 | Bias and variance |\n",
    "| 4 | Regularization and penalties |\n",
    "| 5 | Parameters, hyperparameters, and cross-validation |\n",
    "| 6 | A practical diagnosis workflow and Assignment 3 |\n",
    "\n",
    "We will keep using linear regression, with a short connection back to kNN."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dfb49fc5",
   "metadata": {},
   "source": [
    "## Part 0. Review Assignment 2\n",
    "\n",
    "Open **`day2_assignment_solution.ipynb`**.\n",
    "\n",
    "Assignment 2 showed what simple linear regression learns during `fit()`:\n",
    "\n",
    "- an **intercept**, which moves the line up or down;\n",
    "- a **slope**, which controls how the prediction changes with the input.\n",
    "\n",
    "Today we will calculate additional feature columns such as $x^2$ and $x^3$, then give those\n",
    "columns to the same linear-regression fitting method. This makes the prediction more flexible:\n",
    "it can form a curve when plotted against $x$, while `fit()` still estimates one constant\n",
    "multiplier for each prepared feature column."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "834e82d3",
   "metadata": {},
   "source": [
    "## Part 1. Generalization\n",
    "\n",
    "The purpose of training is not to reproduce the training rows perfectly. The purpose is to make\n",
    "useful predictions for **new rows** from the same problem.\n",
    "\n",
    "- **Training error** measures mistakes on rows used by `fit()`.\n",
    "- **Validation error** measures mistakes on held-out training rows while we choose model settings.\n",
    "- **Test error** is the final estimate, calculated after those choices are finished.\n",
    "- **Generalization** means that the model also works on data it did not train on.\n",
    "\n",
    "A large difference between training and validation performance is called a **generalization\n",
    "gap**. It often warns us that the model has learned details that do not repeat in new data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a95de956",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "training rows: 52\n",
      "test rows:     18\n"
     ]
    }
   ],
   "source": [
    "# NumPy handles arrays, pandas builds result tables, and matplotlib draws the examples.\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# LinearRegression fits squared error; Ridge uses the same weighted-sum prediction but adds a penalty during fitting.\n",
    "from sklearn.linear_model import LinearRegression, Ridge\n",
    "from sklearn.metrics import root_mean_squared_error\n",
    "from sklearn.model_selection import (\n",
    "    GridSearchCV,\n",
    "    KFold,\n",
    "    cross_validate,\n",
    "    train_test_split,\n",
    ")\n",
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.preprocessing import PolynomialFeatures, StandardScaler\n",
    "\n",
    "# A fixed random-number generator makes the noisy dataset reproducible.\n",
    "rng = np.random.default_rng(12)\n",
    "\n",
    "\n",
    "def true_function(x):\n",
    "    \"\"\"The pattern used to create the demonstration data.\"\"\"\n",
    "    return 2 + 0.8 * x - 0.7 * x**2 + 0.15 * x**3\n",
    "\n",
    "\n",
    "# Create one input feature and add random noise to the true pattern.\n",
    "x = np.linspace(-3, 3, 70)\n",
    "y_without_noise = true_function(x)\n",
    "y = y_without_noise + rng.normal(loc=0, scale=1.4, size=len(x))\n",
    "\n",
    "# Scikit-learn expects X to be a table: 70 rows by one feature column.\n",
    "X = x.reshape(-1, 1)\n",
    "\n",
    "# Keep the test set separate before fitting or choosing any model settings.\n",
    "X_train, X_test, y_train, y_test = train_test_split(\n",
    "    X,\n",
    "    y,\n",
    "    test_size=0.25,\n",
    "    random_state=42,\n",
    ")\n",
    "\n",
    "# These folds will be reused so every candidate sees the same validation splits.\n",
    "cv = KFold(n_splits=5, shuffle=True, random_state=42)\n",
    "\n",
    "print(\"training rows:\", len(X_train))\n",
    "print(\"test rows:    \", len(X_test))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "88b61791",
   "metadata": {},
   "source": [
    "### Why use simulated data here?\n",
    "\n",
    "Because we created this small dataset, we know both parts that produced each observation:\n",
    "\n",
    "$$y = \\text{true pattern} + \\text{random noise}.$$\n",
    "\n",
    "In real research data, the true pattern is hidden. Here, knowing it lets us see whether a model\n",
    "learns the pattern or chases the random noise. The test rows still remain separate from model\n",
    "selection."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3f1345ee",
   "metadata": {},
   "outputs": [
    {
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",
      "text/plain": [
       "<Figure size 750x450 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Draw only the training observations; the test points remain hidden for now.\n",
    "grid = np.linspace(-3, 3, 400)\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(7.5, 4.5))\n",
    "ax.scatter(X_train[:, 0], y_train, alpha=0.75, label=\"noisy training observations\")\n",
    "\n",
    "# The dashed curve is available only because this is a simulated teaching example.\n",
    "ax.plot(grid, true_function(grid), \"k--\", linewidth=2, label=\"true pattern\")\n",
    "ax.set_xlabel(\"x\")\n",
    "ax.set_ylabel(\"y\")\n",
    "ax.set_title(\"The observations contain a pattern and random noise\")\n",
    "ax.legend(frameon=False)\n",
    "ax.grid(alpha=0.2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1ab92b51",
   "metadata": {},
   "source": [
    "## Part 2. Model complexity, underfitting, and overfitting\n",
    "\n",
    "The straight line from last session has the form\n",
    "\n",
    "$$\\hat y = b_0+b_1x.$$\n",
    "\n",
    "We can calculate additional feature columns from the original input: $x^2$, $x^3$, and so on.\n",
    "Linear regression then fits\n",
    "\n",
    "$$\\hat y = b_0+b_1x+b_2x^2+b_3x^3+\\cdots+b_dx^d.$$\n",
    "\n",
    "We choose the powers $x,x^2,\\ldots,x^d$ before training. Then `fit()` learns one weight for\n",
    "each power and adds the weighted values together. The powers allow the prediction to form a\n",
    "curve.\n",
    "\n",
    "The setting $d$ is called the **polynomial degree**. We choose it before `fit()`, and it controls\n",
    "how flexible the fitted curve can become.\n",
    "\n",
    "- A model is **underfitting** when it is too simple to learn the main pattern.\n",
    "- A model is **overfitting** when it learns training noise that does not repeat in new data.\n",
    "- **Model complexity** describes how flexible a model is and how many different patterns it can fit."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "3c308ddf",
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_polynomial_model(degree, alpha=0.0):\n",
    "    \"\"\"Build polynomial features followed by scaled linear regression.\"\"\"\n",
    "    # alpha=0 means ordinary least squares: there is no penalty.\n",
    "    # A positive alpha uses Ridge, which we explain in Part 4.\n",
    "    regression = (\n",
    "        LinearRegression()\n",
    "        if alpha == 0\n",
    "        else Ridge(alpha=alpha)\n",
    "    )\n",
    "\n",
    "    # The pipeline learns every step using training rows only.\n",
    "    return Pipeline([\n",
    "        # Calculate fixed columns x, x^2, ..., x^degree before regression fits their multipliers.\n",
    "        (\"powers\", PolynomialFeatures(degree=degree, include_bias=False)),\n",
    "\n",
    "        # Scaling matters when a penalty compares coefficients for differently sized powers.\n",
    "        (\"scale\", StandardScaler()),\n",
    "\n",
    "        # Learn the intercept and one coefficient for each generated column.\n",
    "        (\"regression\", regression),\n",
    "    ])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "d1cbc9ab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>degree</th>\n",
       "      <th>training_RMSE</th>\n",
       "      <th>CV_RMSE</th>\n",
       "      <th>generalization_gap</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2.295</td>\n",
       "      <td>2.402</td>\n",
       "      <td>0.106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3</td>\n",
       "      <td>1.236</td>\n",
       "      <td>1.299</td>\n",
       "      <td>0.064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6</td>\n",
       "      <td>1.132</td>\n",
       "      <td>1.250</td>\n",
       "      <td>0.118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12</td>\n",
       "      <td>0.866</td>\n",
       "      <td>1.511</td>\n",
       "      <td>0.645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>15</td>\n",
       "      <td>0.836</td>\n",
       "      <td>2.271</td>\n",
       "      <td>1.435</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   degree  training_RMSE  CV_RMSE  generalization_gap\n",
       "0       1          2.295    2.402               0.106\n",
       "1       3          1.236    1.299               0.064\n",
       "2       6          1.132    1.250               0.118\n",
       "3      12          0.866    1.511               0.645\n",
       "4      15          0.836    2.271               1.435"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Compare a straight line, the correct cubic shape, and very flexible curves.\n",
    "degrees = [1, 3, 6, 12, 15]\n",
    "degree_rows = []\n",
    "fitted_degree_models = {}\n",
    "\n",
    "for degree in degrees:\n",
    "    model = make_polynomial_model(degree)\n",
    "\n",
    "    # return_train_score=True lets us compare fit on seen and held-out rows.\n",
    "    scores = cross_validate(\n",
    "        model,\n",
    "        X_train,\n",
    "        y_train,\n",
    "        cv=cv,\n",
    "        scoring=\"neg_root_mean_squared_error\",\n",
    "        return_train_score=True,\n",
    "    )\n",
    "\n",
    "    # Scikit-learn negates errors so that \"larger is better\" during model selection.\n",
    "    # We negate them again to report ordinary positive RMSE values.\n",
    "    train_rmse = -scores[\"train_score\"].mean()\n",
    "    cv_rmse = -scores[\"test_score\"].mean()\n",
    "\n",
    "    degree_rows.append({\n",
    "        \"degree\": degree,\n",
    "        \"training_RMSE\": train_rmse,\n",
    "        \"CV_RMSE\": cv_rmse,\n",
    "        \"generalization_gap\": cv_rmse - train_rmse,\n",
    "    })\n",
    "\n",
    "    # Fit on all training rows only for the curves in the next cell.\n",
    "    fitted_degree_models[degree] = model.fit(X_train, y_train)\n",
    "\n",
    "# Lower RMSE is better. A small training error alone is not enough.\n",
    "degree_results = pd.DataFrame(degree_rows)\n",
    "display(degree_results.round(3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "fa3632b7",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1500x420 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot three levels of complexity so the table becomes visible.\n",
    "plot_degrees = [1, 3, 15]\n",
    "fig, axes = plt.subplots(1, 3, figsize=(15, 4.2), sharex=True, sharey=True)\n",
    "\n",
    "grid_table = grid.reshape(-1, 1)\n",
    "for ax, degree in zip(axes, plot_degrees):\n",
    "    model = fitted_degree_models[degree]\n",
    "\n",
    "    ax.scatter(X_train[:, 0], y_train, s=24, alpha=0.65, label=\"training data\")\n",
    "    ax.plot(grid, true_function(grid), \"k--\", linewidth=2, label=\"true pattern\")\n",
    "    ax.plot(grid, model.predict(grid_table), linewidth=2, label=\"fitted curve\")\n",
    "    ax.set_title(f\"degree = {degree}\")\n",
    "    ax.set_xlabel(\"x\")\n",
    "    ax.grid(alpha=0.2)\n",
    "\n",
    "axes[0].set_ylabel(\"y\")\n",
    "axes[0].legend(frameon=False, fontsize=9)\n",
    "fig.suptitle(\"Too simple, appropriate, and too flexible\", y=1.03)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fca9b454",
   "metadata": {},
   "source": [
    "### Read the training and validation errors together\n",
    "\n",
    "- Degree 1 has relatively high training and validation error. It cannot bend enough, so it has\n",
    "  **underfit** the curved pattern.\n",
    "- A moderate degree follows the main pattern and keeps validation error low.\n",
    "- A very high degree reduces training error, but its validation error and generalization gap\n",
    "  increase. It has started to **overfit**.\n",
    "\n",
    "The same complexity idea applies to kNN from Day 2:\n",
    "\n",
    "| kNN setting | Flexibility | Common risk |\n",
    "|---|---|---|\n",
    "| very small $k$ | follows small local details | high variance and overfitting |\n",
    "| moderate $k$ | balances local detail and smoothing | often generalizes better |\n",
    "| very large $k$ | averages over a large neighbourhood | high bias and underfitting |\n",
    "\n",
    "The direction is reversed: increasing polynomial degree makes regression more flexible, while\n",
    "increasing $k$ makes kNN smoother and less flexible."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cea0e083",
   "metadata": {},
   "source": [
    "## Part 3. Bias and variance\n",
    "\n",
    "Bias and variance describe two different problems:\n",
    "\n",
    "- **Bias:** the model repeatedly misses the main pattern in the same way.\n",
    "- **Variance:** the fitted model changes too much when the training rows change.\n",
    "- **Noise:** random variation that the available features cannot explain.\n",
    "\n",
    "| What we see | Likely problem |\n",
    "|---|---|\n",
    "| training and validation errors are both high | high bias: the model is too simple |\n",
    "| training error is low but validation error is worse or unstable | high variance: the model is too sensitive |\n",
    "\n",
    "### Visual 1: the trade-off as complexity increases\n",
    "\n",
    "<img src=\"../figures/bias_variance_total_error_cc0.svg\"\n",
    "     alt=\"Bias decreases and variance increases as model complexity grows; total error is lowest between the two extremes\"\n",
    "     width=\"760\">\n",
    "\n",
    "Read the figure from left to right:\n",
    "\n",
    "1. A very simple model has high bias because it cannot follow the pattern.\n",
    "2. More flexibility reduces bias, but variance begins to grow.\n",
    "3. A very flexible model has high variance because it follows training details too closely.\n",
    "4. Total new-data error is often lowest between the two extremes.\n",
    "\n",
    "*Figure: “Bias and variance contributing to total error,” Bigbossfarin,\n",
    "[Wikimedia Commons](https://commons.wikimedia.org/wiki/File:Bias_and_variance_contributing_to_total_error.svg),\n",
    "CC0 1.0.*\n",
    "\n",
    "A common summary for squared prediction error is\n",
    "\n",
    "$$\\text{expected new-data error}\n",
    "= \\text{bias}^2 + \\text{variance} + \\text{noise}.$$\n",
    "\n",
    "We do not know these three parts exactly in a real project. Cross-validation helps us compare\n",
    "settings and look for a useful balance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "008f90ab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x450 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Resample only X_train/y_train; the original split and test set stay unchanged.\n",
    "bootstrap_rng = np.random.default_rng(123)\n",
    "bootstrap_indices = [\n",
    "    # A temporary sample may repeat some training rows and omit others.\n",
    "    bootstrap_rng.integers(0, len(X_train), size=len(X_train))\n",
    "    for repeat in range(20)\n",
    "]\n",
    "\n",
    "# Focus on the central x range so differences between curves remain readable.\n",
    "focus_grid = np.linspace(-2.5, 2.5, 300)\n",
    "focus_table = focus_grid.reshape(-1, 1)\n",
    "inside_focus = (\n",
    "    (X_train[:, 0] >= focus_grid.min())\n",
    "    & (X_train[:, 0] <= focus_grid.max())\n",
    ")\n",
    "\n",
    "# Compare a model that is too simple, a useful middle case, and a flexible model.\n",
    "degrees_to_show = [1, 3, 10]\n",
    "panel_titles = [\n",
    "    \"degree 1: high bias\",\n",
    "    \"degree 3: balanced\",\n",
    "    \"degree 10: high variance\",\n",
    "]\n",
    "\n",
    "fig, axes = plt.subplots(1, 3, figsize=(15, 4.5), sharex=True, sharey=True)\n",
    "\n",
    "for ax, degree, title in zip(axes, degrees_to_show, panel_titles):\n",
    "    predictions = []\n",
    "\n",
    "    for row_indices in bootstrap_indices:\n",
    "        # Each temporary sample produces one thin blue fitted curve.\n",
    "        resampled_model = make_polynomial_model(degree)\n",
    "        resampled_model.fit(X_train[row_indices], y_train[row_indices])\n",
    "        predictions.append(resampled_model.predict(focus_table))\n",
    "\n",
    "    predictions = np.asarray(predictions)\n",
    "    average_prediction = predictions.mean(axis=0)\n",
    "\n",
    "    # Blue-curve spread shows variance: wider spread means higher variance.\n",
    "    for one_prediction in predictions:\n",
    "        ax.plot(focus_grid, one_prediction, color=\"tab:blue\", alpha=0.16)\n",
    "\n",
    "    # The red-to-black gap shows bias: a larger gap means higher bias.\n",
    "    ax.plot(\n",
    "        focus_grid,\n",
    "        average_prediction,\n",
    "        color=\"tab:red\",\n",
    "        linewidth=2.5,\n",
    "        label=\"average fitted curve\",\n",
    "    )\n",
    "    ax.plot(\n",
    "        focus_grid,\n",
    "        true_function(focus_grid),\n",
    "        \"k--\",\n",
    "        linewidth=2,\n",
    "        label=\"true pattern\",\n",
    "    )\n",
    "    ax.scatter(\n",
    "        X_train[inside_focus, 0],\n",
    "        y_train[inside_focus],\n",
    "        s=16,\n",
    "        color=\"tab:orange\",\n",
    "        alpha=0.4,\n",
    "        label=\"training observations\",\n",
    "    )\n",
    "\n",
    "    ax.set_title(title)\n",
    "    ax.set_xlabel(\"x\")\n",
    "    ax.set_xlim(-2.5, 2.5)\n",
    "    ax.set_ylim(-11, 6)\n",
    "    ax.grid(alpha=0.2)\n",
    "\n",
    "axes[0].set_ylabel(\"y\")\n",
    "axes[0].legend(frameon=False, fontsize=8)\n",
    "fig.suptitle(\"Bias is the systematic miss; variance is the spread across fitted curves\")\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e293164",
   "metadata": {},
   "source": [
    "### Read the three panels\n",
    "\n",
    "- **Degree 1:** blue curves are close, but red misses black → high bias.\n",
    "- **Degree 3:** blue curves are close and red follows black → balanced.\n",
    "- **Degree 10:** blue curves spread apart → high variance.\n",
    "\n",
    "> Blue spread shows variance; the red-to-black gap shows bias. Resampling uses only the original\n",
    "> training set; the test set and original arrays stay unchanged."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1a751ca6",
   "metadata": {},
   "source": [
    "## Part 4. Regularization and penalties\n",
    "\n",
    "**Regularization** discourages unnecessarily extreme fitted coefficients. Instead of minimizing\n",
    "only squared training error, regularized regression minimizes\n",
    "\n",
    "$$\\text{training objective}\n",
    "= \\mathrm{MSE} + \\alpha\\sum_{j=1}^{p}b_j^2.$$\n",
    "\n",
    "The second term is an **L2 penalty**. The number $\\alpha$ controls its strength:\n",
    "\n",
    "- $\\alpha=0$: no penalty, so this is ordinary least squares;\n",
    "- small positive $\\alpha$: gently shrink the coefficients;\n",
    "- very large $\\alpha$: strongly shrink them and risk underfitting.\n",
    "\n",
    "The intercept is not included in the penalty. We standardize the generated features first so\n",
    "one coefficient is not penalized differently only because its column uses larger units.\n",
    "\n",
    "| Penalty | Form | Main effect |\n",
    "|---|---|---|\n",
    "| L2, used by Ridge | $\\sum_jb_j^2$ | shrinks coefficients toward zero |\n",
    "| L1, used by Lasso | $\\sum_j|b_j|$ | can make some coefficients exactly zero |\n",
    "\n",
    "We will demonstrate only L2. The main concept is the penalty."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "779b665b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>alpha</th>\n",
       "      <th>training_RMSE</th>\n",
       "      <th>CV_RMSE</th>\n",
       "      <th>coefficient_size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.000</td>\n",
       "      <td>0.866</td>\n",
       "      <td>1.511</td>\n",
       "      <td>708.951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.001</td>\n",
       "      <td>1.012</td>\n",
       "      <td>1.251</td>\n",
       "      <td>59.881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.010</td>\n",
       "      <td>1.074</td>\n",
       "      <td>1.313</td>\n",
       "      <td>11.106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.100</td>\n",
       "      <td>1.095</td>\n",
       "      <td>1.243</td>\n",
       "      <td>3.764</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.000</td>\n",
       "      <td>1.124</td>\n",
       "      <td>1.200</td>\n",
       "      <td>2.773</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>10.000</td>\n",
       "      <td>1.272</td>\n",
       "      <td>1.335</td>\n",
       "      <td>1.951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>100.000</td>\n",
       "      <td>1.915</td>\n",
       "      <td>1.926</td>\n",
       "      <td>0.998</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     alpha  training_RMSE  CV_RMSE  coefficient_size\n",
       "0    0.000          0.866    1.511           708.951\n",
       "1    0.001          1.012    1.251            59.881\n",
       "2    0.010          1.074    1.313            11.106\n",
       "3    0.100          1.095    1.243             3.764\n",
       "4    1.000          1.124    1.200             2.773\n",
       "5   10.000          1.272    1.335             1.951\n",
       "6  100.000          1.915    1.926             0.998"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Keep the polynomial degree deliberately high and change only penalty strength.\n",
    "regularization_alphas = [0.0, 0.001, 0.01, 0.1, 1.0, 10.0, 100.0]\n",
    "regularization_rows = []\n",
    "fitted_regularized_models = {}\n",
    "\n",
    "for alpha in regularization_alphas:\n",
    "    model = make_polynomial_model(degree=12, alpha=alpha)\n",
    "\n",
    "    scores = cross_validate(\n",
    "        model,\n",
    "        X_train,\n",
    "        y_train,\n",
    "        cv=cv,\n",
    "        scoring=\"neg_root_mean_squared_error\",\n",
    "        return_train_score=True,\n",
    "    )\n",
    "\n",
    "    # Fit on all training rows so we can inspect the learned coefficient sizes.\n",
    "    model.fit(X_train, y_train)\n",
    "    coefficients = model.named_steps[\"regression\"].coef_\n",
    "\n",
    "    regularization_rows.append({\n",
    "        \"alpha\": alpha,\n",
    "        \"training_RMSE\": -scores[\"train_score\"].mean(),\n",
    "        \"CV_RMSE\": -scores[\"test_score\"].mean(),\n",
    "\n",
    "        # The L2 norm summarizes the overall size of all polynomial coefficients.\n",
    "        \"coefficient_size\": np.linalg.norm(coefficients),\n",
    "    })\n",
    "    fitted_regularized_models[alpha] = model\n",
    "\n",
    "regularization_results = pd.DataFrame(regularization_rows)\n",
    "display(regularization_results.round(3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "6f7a30e9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x420 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Show both effects of alpha: validation error and coefficient shrinkage.\n",
    "positions = np.arange(len(regularization_results))\n",
    "alpha_labels = [str(value) for value in regularization_results[\"alpha\"]]\n",
    "\n",
    "fig, axes = plt.subplots(1, 2, figsize=(12, 4))\n",
    "\n",
    "axes[0].plot(positions, regularization_results[\"CV_RMSE\"], marker=\"o\")\n",
    "axes[0].set_xticks(positions, alpha_labels, rotation=35)\n",
    "axes[0].set_xlabel(\"penalty strength, alpha\")\n",
    "axes[0].set_ylabel(\"mean cross-validation RMSE\")\n",
    "axes[0].set_title(\"Too little or too much penalty can hurt\")\n",
    "axes[0].grid(alpha=0.25)\n",
    "\n",
    "axes[1].plot(positions, regularization_results[\"coefficient_size\"], marker=\"o\")\n",
    "axes[1].set_xticks(positions, alpha_labels, rotation=35)\n",
    "axes[1].set_xlabel(\"penalty strength, alpha\")\n",
    "axes[1].set_ylabel(\"overall coefficient size\")\n",
    "axes[1].set_title(\"A stronger penalty shrinks coefficients\")\n",
    "axes[1].grid(alpha=0.25)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "# Compare the fitted shapes for no, moderate, and very strong regularization.\n",
    "fig, axes = plt.subplots(1, 3, figsize=(15, 4.2), sharex=True, sharey=True)\n",
    "for ax, alpha in zip(axes, [0.0, 1.0, 100.0]):\n",
    "    model = fitted_regularized_models[alpha]\n",
    "    ax.scatter(X_train[:, 0], y_train, s=22, alpha=0.6)\n",
    "    ax.plot(grid, true_function(grid), \"k--\", linewidth=2, label=\"true pattern\")\n",
    "    ax.plot(grid, model.predict(grid_table), linewidth=2, label=\"fitted curve\")\n",
    "    ax.set_title(f\"degree 12, alpha = {alpha:g}\")\n",
    "    ax.set_xlabel(\"x\")\n",
    "    ax.grid(alpha=0.2)\n",
    "\n",
    "axes[0].set_ylabel(\"y\")\n",
    "axes[0].legend(frameon=False, fontsize=9)\n",
    "fig.suptitle(\"Regularization controls a flexible model without changing its degree\", y=1.03)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "781376a1",
   "metadata": {},
   "source": [
    "Regularization creates another trade-off:\n",
    "\n",
    "- too little penalty allows high variance;\n",
    "- a moderate penalty can reduce variance and improve validation error;\n",
    "- too much penalty makes the model too rigid and increases bias.\n",
    "\n",
    "Regularization does not guarantee a better model. Its strength must be treated as a setting to\n",
    "choose with validation data, not as a number that we increase without limit."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eda20393",
   "metadata": {},
   "source": [
    "## Part 5. Parameters, hyperparameters, and cross-validation\n",
    "\n",
    "These words describe who chooses a quantity:\n",
    "\n",
    "| Term | Who chooses it? | Examples |\n",
    "|---|---|---|\n",
    "| **parameter** | learned by `fit()` from training data | intercept and regression coefficients |\n",
    "| **hyperparameter** | chosen by us before fitting | polynomial degree, penalty strength $\\alpha$, kNN neighbour count $k$ |\n",
    "| **metric** | chosen by us to define useful performance | RMSE for this regression problem |\n",
    "\n",
    "We should not choose degree or $\\alpha$ by repeatedly checking the test set. As in Day 2, use\n",
    "cross-validation on the training data, select the hyperparameters, refit on all training rows,\n",
    "and then use the test set once."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "8463de9c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "selected hyperparameters: {'powers__degree': 12, 'regression__alpha': 1.0}\n",
      "best mean CV RMSE: 1.200\n",
      "final test RMSE: 1.476\n"
     ]
    }
   ],
   "source": [
    "# Build one regularized linear-regression pipeline for the search.\n",
    "# Ridge also accepts alpha=0, which represents the no-penalty candidate here.\n",
    "search_model = Pipeline([\n",
    "    (\"powers\", PolynomialFeatures(include_bias=False)),\n",
    "    (\"scale\", StandardScaler()),\n",
    "    (\"regression\", Ridge()),\n",
    "])\n",
    "\n",
    "# Compare model flexibility and penalty strength together.\n",
    "parameter_grid = {\n",
    "    \"powers__degree\": [1, 2, 3, 5, 8, 12],\n",
    "    \"regression__alpha\": [0.0, 0.001, 0.01, 0.1, 1.0, 10.0],\n",
    "}\n",
    "\n",
    "# The negative sign follows scikit-learn's \"larger is better\" scoring convention.\n",
    "search = GridSearchCV(\n",
    "    search_model,\n",
    "    param_grid=parameter_grid,\n",
    "    cv=cv,\n",
    "    scoring=\"neg_root_mean_squared_error\",\n",
    ")\n",
    "\n",
    "# Every choice is made with training folds; X_test is still untouched.\n",
    "search.fit(X_train, y_train)\n",
    "\n",
    "print(\"selected hyperparameters:\", search.best_params_)\n",
    "print(f\"best mean CV RMSE: {-search.best_score_:.3f}\")\n",
    "\n",
    "# GridSearchCV automatically refits the selected settings on all training rows.\n",
    "selected_model = search.best_estimator_\n",
    "\n",
    "# Now use the test set once for the final estimate.\n",
    "test_predictions = selected_model.predict(X_test)\n",
    "final_test_rmse = root_mean_squared_error(y_test, test_predictions)\n",
    "print(f\"final test RMSE: {final_test_rmse:.3f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "afba77f3",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 800x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# After the final evaluation, show the test rows and the selected fitted curve.\n",
    "fig, ax = plt.subplots(figsize=(8, 4.8))\n",
    "ax.scatter(X_train[:, 0], y_train, alpha=0.65, label=\"training rows\")\n",
    "ax.scatter(X_test[:, 0], y_test, marker=\"x\", s=70, label=\"test rows\")\n",
    "ax.plot(grid, true_function(grid), \"k--\", linewidth=2, label=\"true pattern\")\n",
    "ax.plot(\n",
    "    grid,\n",
    "    selected_model.predict(grid_table),\n",
    "    linewidth=2.5,\n",
    "    label=\"CV-selected model\",\n",
    ")\n",
    "ax.set_xlabel(\"x\")\n",
    "ax.set_ylabel(\"y\")\n",
    "ax.set_title(\"Select with cross-validation, then evaluate the test set once\")\n",
    "ax.legend(frameon=False)\n",
    "ax.grid(alpha=0.2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a511bffc",
   "metadata": {},
   "source": [
    "### Prediction settings are not physical truth\n",
    "\n",
    "In this run, cross-validation may select a flexible degree together with a moderate penalty.\n",
    "That does **not** prove that the real process is a polynomial of that degree. It only says that\n",
    "this combination predicted the held-out folds well among the candidates we compared.\n",
    "\n",
    "Hyperparameters describe how we fit a predictive model. A scientific explanation needs domain\n",
    "knowledge, measurement design, uncertainty analysis, and evidence beyond one CV result."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6aebe893",
   "metadata": {},
   "source": [
    "## Part 6. A practical diagnosis workflow\n",
    "\n",
    "Read training and validation results together before deciding what to change.\n",
    "\n",
    "| What you observe | Likely problem | Reasonable next step |\n",
    "|---|---|---|\n",
    "| training and validation errors are both high | high bias / underfitting | add useful flexibility, improve features, or reduce excessive regularization |\n",
    "| training error is low but validation error is much higher | high variance / overfitting | simplify, regularize, or collect more representative data |\n",
    "| validation results change greatly across folds | unstable estimate or limited data | report the variation and collect more data if possible |\n",
    "| training and validation errors are close and acceptable | reasonable balance | finish selection, then evaluate the test set once |\n",
    "\n",
    "More data often helps a high-variance model. More data usually does not repair a model whose\n",
    "features or assumptions are too simple to represent the real pattern.\n",
    "\n",
    "### Terms to take away\n",
    "\n",
    "- **generalization:** performance on new data;\n",
    "- **model complexity:** how flexible a pattern the model can learn;\n",
    "- **underfitting / high bias:** too simple;\n",
    "- **overfitting / high variance:** too sensitive to training details;\n",
    "- **regularization:** add a penalty to discourage unnecessary complexity;\n",
    "- **parameter:** learned during `fit()`;\n",
    "- **hyperparameter:** selected using validation or cross-validation."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e995fc39",
   "metadata": {},
   "source": [
    "## Assignment 3: diagnose model complexity (about 25 minutes)\n",
    "\n",
    "Use the same synthetic training data and five folds. Do **not** use `X_test` or `y_test` in this\n",
    "assignment.\n",
    "\n",
    "Complete two pieces of code:\n",
    "\n",
    "1. `evaluate_setting` returns training RMSE, cross-validation RMSE, and their gap for one degree\n",
    "   and one penalty strength.\n",
    "2. Build and sort a comparison table for the five supplied settings.\n",
    "\n",
    "Then explain which setting underfits, which setting overfits, and what the penalty changes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c5a60d71",
   "metadata": {},
   "outputs": [],
   "source": [
    "# These candidates isolate the effects of complexity and regularization.\n",
    "assignment_settings = [\n",
    "    {\"degree\": 1, \"alpha\": 0.0},\n",
    "    {\"degree\": 3, \"alpha\": 0.0},\n",
    "    {\"degree\": 12, \"alpha\": 0.0},\n",
    "    {\"degree\": 12, \"alpha\": 1.0},\n",
    "    {\"degree\": 12, \"alpha\": 100.0},\n",
    "]\n",
    "\n",
    "\n",
    "def evaluate_setting(degree, alpha):\n",
    "    \"\"\"Return training and CV errors for one model setting.\"\"\"\n",
    "    # TODO 1: build the model with make_polynomial_model(degree, alpha).\n",
    "    # TODO 2: use cross_validate with X_train, y_train, cv, RMSE scoring,\n",
    "    #         and return_train_score=True.\n",
    "    # TODO 3: return a dictionary with degree, alpha, training_RMSE, CV_RMSE,\n",
    "    #         and generalization_gap.\n",
    "    pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "85b13d2b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# TODO 4: call evaluate_setting once for every dictionary in assignment_settings.\n",
    "assignment_rows = []\n",
    "\n",
    "# TODO 5: create assignment_results from assignment_rows.\n",
    "# Sort from the lowest CV_RMSE to the highest CV_RMSE.\n",
    "assignment_results = None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "afb289cb",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Run this checker after completing the assignment code.\n",
    "assert assignment_results is not None, \"assignment_results has not been created\"\n",
    "assert list(assignment_results.columns) == [\n",
    "    \"degree\",\n",
    "    \"alpha\",\n",
    "    \"training_RMSE\",\n",
    "    \"CV_RMSE\",\n",
    "    \"generalization_gap\",\n",
    "]\n",
    "assert len(assignment_results) == len(assignment_settings)\n",
    "assert assignment_results[\"CV_RMSE\"].is_monotonic_increasing\n",
    "print(\"OK: the comparison table has the expected structure\")\n",
    "display(assignment_results.round(3))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6392a481",
   "metadata": {},
   "source": [
    "**Answer in a new markdown cell using four or five sentences.**\n",
    "\n",
    "1. Which setting shows the clearest underfitting? Use training and CV RMSE as evidence.\n",
    "2. Which setting shows the clearest overfitting? Use the generalization gap as evidence.\n",
    "3. What changed when a moderate penalty was added to degree 12?\n",
    "4. Why should the final choice use CV RMSE rather than training RMSE?\n",
    "\n",
    "**Optional challenge:** draw CV RMSE against the five settings and label the lowest point."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "544de551",
   "metadata": {},
   "source": [
    "## Recap\n",
    "\n",
    "- A low training error does not guarantee useful predictions on new data.\n",
    "- Complexity that is too low causes underfitting and high bias.\n",
    "- Complexity that is too high can cause overfitting and high variance.\n",
    "- Regularization adds a penalty that can stabilize a flexible model.\n",
    "- Excessive regularization can return us to high bias.\n",
    "- Parameters are learned by `fit()`; hyperparameters are selected with validation data.\n",
    "- Cross-validation supports those choices while the test set remains untouched.\n",
    "\n",
    "The goal is not the most complicated model or the smallest training error. The goal is a model\n",
    "whose assumptions, complexity, and validation performance support reliable generalization.\n",
    "\n",
    "### Continue learning\n",
    "\n",
    "For more workshops and self-study materials in scientific computing, data science, and high-performance computing, visit the [SciNet Education site](https://education.scinet.utoronto.ca/).\n"
   ]
  }
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