{"cells": [{"attachments": {}, "cell_type": "markdown", "metadata": {"pycharm": {"name": "#%% md\n"}}, "source": ["# Pool-based Active Learning - Simple Evaluation Study"]}, {"cell_type": "markdown", "metadata": {}, "source": ["> **_Google Colab Note:_** If the notebook fails to run after installing the needed packages, try to restart the runtime (Ctrl + M) under Runtime -> Restart session.\n", "\n", "[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/scikit-activeml/scikit-activeml.github.io/blob/gh-pages/development/generated/tutorials_colab//04_pool_simple_evaluation_study.ipynb)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["**Notebook Dependencies**\n", "\n", "Uncomment the following cells to install all dependencies for this tutorial."]}, {"cell_type": "code", "metadata": {"ExecuteTime": {"end_time": "2025-11-26T12:07:50.203876Z", "start_time": "2025-11-26T12:07:50.202175Z"}}, "source": ["# !pip install scikit-activeml"], "outputs": [], "execution_count": 1}, {"cell_type": "markdown", "metadata": {}, "source": ["
"]}, {"attachments": {}, "cell_type": "markdown", "metadata": {"collapsed": false, "jupyter": {"outputs_hidden": false}}, "source": "The main purpose of this tutorial is to show how a simple comparison study can be realized using `scikit-activeml`. For this experiment, we use a repeated K-fold cross-validation to evaluate the query strategies using two different classifiers. Our main focus is cleanly separating the repetitions, proper handling of random states and separation of test and training data."}, {"cell_type": "code", "metadata": {"collapsed": false, "jupyter": {"outputs_hidden": false}, "pycharm": {"name": "#%%\n"}, "ExecuteTime": {"end_time": "2025-11-26T12:07:51.952114Z", "start_time": "2025-11-26T12:07:50.244692Z"}}, "source": ["import numpy as np\n", "import matplotlib as mpl\n", "import matplotlib.pyplot as plt\n", "\n", "from sklearn.gaussian_process import GaussianProcessClassifier\n", "from sklearn.datasets import load_iris\n", "from sklearn.model_selection import StratifiedKFold, KFold\n", "from sklearn.preprocessing import StandardScaler\n", "\n", "from skactiveml.classifier import SklearnClassifier, ParzenWindowClassifier\n", "from skactiveml.pool import UncertaintySampling, ProbabilisticAL, RandomSampling\n", "from skactiveml.utils import call_func, MISSING_LABEL\n", "\n", "import warnings\n", "mpl.rcParams[\"figure.facecolor\"] = \"white\"\n", "warnings.filterwarnings(\"ignore\")"], "outputs": [], "execution_count": 2}, {"attachments": {}, "cell_type": "markdown", "metadata": {}, "source": ["## Random Seed Management\n", "To guarantee that the experiment is reproducible, we have to set the random states for all components that might use one. To simplify this, we make all random seeds dependent of a single fixed random state and use helper functions to generate new seeds and random states. Keep in mind that the `master_random_state` should only be used to create new random states or random seeds."]}, {"cell_type": "code", "metadata": {"ExecuteTime": {"end_time": "2025-11-26T12:07:52.000286Z", "start_time": "2025-11-26T12:07:51.998126Z"}}, "source": ["master_random_state = np.random.RandomState(0)\n", "\n", "def gen_seed(random_state:np.random.RandomState):\n", " return random_state.randint(0, 2**31)\n", "\n", "def gen_random_state(random_state:np.random.RandomState):\n", " return np.random.RandomState(gen_seed(random_state))"], "outputs": [], "execution_count": 3}, {"attachments": {}, "cell_type": "markdown", "metadata": {"collapsed": false, "jupyter": {"outputs_hidden": false}}, "source": ["## Data Set\n", "The code loads the classic Iris dataset, which contains measurements of flower characteristics such as sepal length, sepal width, petal length, and petal width. These measurements are stored in `X`, while the corresponding species labels (setosa, versicolor, virginica) are returned in `y_true`. The unique species labels are extracted with `np.unique`, and `n_classes` records how many distinct species are present in the dataset."]}, {"cell_type": "code", "metadata": {"ExecuteTime": {"end_time": "2025-11-26T12:07:52.042796Z", "start_time": "2025-11-26T12:07:52.040145Z"}}, "source": ["X, y_true = load_iris(return_X_y=True)\n", "classes = np.unique(y_true)\n", "n_classes = len(classes)"], "outputs": [], "execution_count": 4}, {"attachments": {}, "cell_type": "markdown", "metadata": {}, "source": ["## Classification Models and Query Strategies\n", "We handle the creation of classifiers and query strategies using factory functions to simplify the separation of classifiers and query strategies across repetitions and folds."]}, {"cell_type": "code", "metadata": {"ExecuteTime": {"end_time": "2025-11-26T12:07:52.085731Z", "start_time": "2025-11-26T12:07:52.083175Z"}}, "source": ["classifier_factory_functions = {\n", " 'ParzenWindowClassifier': lambda classes, random_state: ParzenWindowClassifier(\n", " classes=classes,\n", " random_state=gen_seed(random_state),\n", " metric='rbf',\n", " metric_dict={'gamma':'mean'},\n", " class_prior=1e-3,\n", " ),\n", " 'GaussianProcessClassifier': lambda classes, random_state: SklearnClassifier(\n", " GaussianProcessClassifier(random_state=gen_seed(random_state)),\n", " classes=classes,\n", " random_state=gen_seed(random_state)\n", " )\n", "}\n", "\n", "query_strategy_factory_functions = {\n", " 'RandomSampling': lambda random_state: RandomSampling(random_state=gen_seed(random_state)),\n", " 'UncertaintySampling': lambda random_state: UncertaintySampling(random_state=gen_seed(random_state)),\n", " 'ProbabilisticAL': lambda random_state: ProbabilisticAL(random_state=gen_seed(random_state), metric='rbf')\n", "}\n", "\n", "def create_classifier(name, classes, random_state):\n", " return classifier_factory_functions[name](classes, random_state)\n", "\n", "def create_query_strategy(name, random_state):\n", " return query_strategy_factory_functions[name](random_state)"], "outputs": [], "execution_count": 5}, {"attachments": {}, "cell_type": "markdown", "metadata": {}, "source": ["## Experiment Parameters"]}, {"attachments": {}, "cell_type": "markdown", "metadata": {}, "source": ["For this experiment, we need to define how the strategies should be compared against one another. As we want to use a repeated K-Fold Cross-validation, we need to define the number of repetitions (`n_reps`), the number of folds (`n_folds`) and the number of queries within each fold. Furthermore, we have the option of using stratified Cross-validation."]}, {"cell_type": "code", "metadata": {"ExecuteTime": {"end_time": "2025-11-26T12:07:52.128992Z", "start_time": "2025-11-26T12:07:52.127224Z"}}, "source": ["n_reps = 5\n", "n_folds = 5\n", "n_cycles = 50\n", "use_stratified = True\n", "classifier_names = classifier_factory_functions.keys()\n", "query_strategy_names = query_strategy_factory_functions.keys()"], "outputs": [], "execution_count": 6}, {"attachments": {}, "cell_type": "markdown", "metadata": {}, "source": ["## Experiment Loop"]}, {"attachments": {}, "cell_type": "markdown", "metadata": {}, "source": ["The actual experiment loops over all query strategy and classifier combinations. The average accuracy over the test set is recorded for each cycle and stored in the `results` dictionary."]}, {"cell_type": "code", "metadata": {"ExecuteTime": {"end_time": "2025-11-26T12:09:02.249272Z", "start_time": "2025-11-26T12:07:52.170335Z"}}, "source": ["results = {}\n", "kfold_class = StratifiedKFold if use_stratified else KFold\n", "\n", "for clf_name in classifier_names:\n", " for qs_name in query_strategy_names:\n", " accuracies = np.full((n_reps, n_folds, n_cycles), np.nan)\n", " for i_rep in range(n_reps):\n", " kf = kfold_class(n_splits=n_folds, shuffle=True, random_state=gen_seed(master_random_state))\n", " for i_fold, (train_idx, test_idx) in enumerate(kf.split(X, y_true)):\n", " X_test = X[test_idx]\n", " y_test = y_true[test_idx]\n", "\n", " X_train = X[train_idx]\n", " y_train_true = y_true[train_idx]\n", " y_train = np.full(shape=y_train_true.shape, fill_value=MISSING_LABEL)\n", "\n", " sc = StandardScaler().fit(X_train)\n", " X_train = sc.transform(X_train)\n", " X_test = sc.transform(X_test)\n", "\n", " clf = create_classifier(clf_name, classes, gen_random_state(master_random_state))\n", " qs = create_query_strategy(qs_name, gen_random_state(master_random_state))\n", "\n", " clf.fit(X_train, y_train)\n", " for c in range(n_cycles):\n", " query_idx = call_func(qs.query, X=X_train, y=y_train, clf=clf, batch_size=1)\n", " y_train[query_idx] = y_train_true[query_idx]\n", " clf.fit(X_train, y_train)\n", " accuracies[i_rep, i_fold, c] = clf.score(X_test, y_test)\n", " results[(clf_name, qs_name)] = accuracies"], "outputs": [], "execution_count": 7}, {"attachments": {}, "cell_type": "markdown", "metadata": {}, "source": ["## Result Plotting\n", "We use learning curves to compare the strategies. For that, we plot the average accuracy (averaged over all repetitions and folds) relative to the number of queries. The error bars show the standard deviation for each curve. Furthermore, the legend shows the area under the learning curve, i.e., mean accuracy over all cycles."]}, {"cell_type": "code", "metadata": {"ExecuteTime": {"end_time": "2025-11-26T12:09:02.488100Z", "start_time": "2025-11-26T12:09:02.335035Z"}}, "source": ["for clf_name in classifier_names:\n", " for qs_name in query_strategy_names:\n", " key = (clf_name, qs_name)\n", " result = results[key]\n", " reshaped_result = result.reshape((-1, n_cycles))\n", " errorbar_mean = np.mean(reshaped_result, axis=0)\n", " errorbar_std = np.std(reshaped_result, axis=0)\n", " label = f\"({np.mean(errorbar_mean):.4f}) {qs_name}\"\n", " plt.plot(np.arange(n_cycles), errorbar_mean, label=label)\n", " plt.fill_between(np.arange(n_cycles), errorbar_mean-errorbar_std, errorbar_mean+errorbar_std, alpha=0.2)\n", " plt.title(clf_name)\n", " plt.legend(loc='lower right')\n", " plt.xlabel('cycle')\n", " plt.ylabel('accuracy')\n", " plt.show()"], "outputs": [{"data": {"text/plain": ["
"], "image/png": "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"}, "metadata": {}, "output_type": "display_data", "jetTransient": {"display_id": null}}, {"data": {"text/plain": ["
"], "image/png": "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"}, "metadata": {}, "output_type": "display_data", "jetTransient": {"display_id": null}}], "execution_count": 8}], "metadata": {"kernelspec": {"display_name": "skaml", "language": "python", "name": "python3"}, "language_info": {"codemirror_mode": {"name": "ipython", "version": 3}, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.12.9"}, "nbsphinx": {"orphan": true}}, "nbformat": 4, "nbformat_minor": 4}