{"cells": [{"cell_type": "markdown", "metadata": {}, "source": ["# Stream-based Active Learning - Getting Started"]}, {"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/1.0/generated/tutorials_colab//20_stream_getting_started.ipynb)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["**Notebook Dependencies**\n", "\n", "Uncomment the following cells to install all dependencies for this tutorial."]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["# !pip install scikit-activeml[opt] torch torchvision datasets sentence_transformers"]}, {"cell_type": "markdown", "metadata": {}, "source": ["
"]}, {"cell_type": "markdown", "metadata": {}, "source": ["In this notebook, we will show how stream-based active learning strategies are used and compared them to one another. We showcase the methods available in the `skactiveml` stream package. "]}, {"cell_type": "code", "execution_count": 2, "metadata": {"ExecuteTime": {"end_time": "2025-11-25T15:04:58.409315Z", "start_time": "2025-11-25T15:04:54.870314Z"}}, "outputs": [], "source": ["import numpy as np\n", "import torch\n", "import matplotlib as mlp\n", "import matplotlib.pyplot as plt\n", "\n", "from datasets import load_dataset\n", "from collections import deque\n", "from scipy.ndimage import gaussian_filter1d\n", "from sentence_transformers import SentenceTransformer\n", "from skactiveml.classifier import ParzenWindowClassifier\n", "from skactiveml.stream import StreamRandomSampling, PeriodicSampling\n", "from skactiveml.stream import (\n", " FixedUncertainty,\n", " VariableUncertainty,\n", " Split,\n", " StreamProbabilisticAL,\n", " StreamDensityBasedAL,\n", " CognitiveDualQueryStrategyRan,\n", " CognitiveDualQueryStrategyFixUn,\n", " CognitiveDualQueryStrategyRanVarUn,\n", " CognitiveDualQueryStrategyVarUn,\n", ")\n", "from skactiveml.utils import call_func\n", "\n", "# Define the device depending on its availability.\n", "device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n", "mlp.rcParams[\"figure.facecolor\"] = \"white\""]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Initialize Stream Parameters\n", "Before the experiments can start, we need to construct a random data set. For this, we specify the necessary parameters in the cell below. We specify the size of the sliding window that defines the available training data (`training_size`). Additionally, we define a parameter (`fit_clf`) to decide if `X` and `y` are needed and should be used."]}, {"cell_type": "code", "execution_count": 3, "metadata": {"ExecuteTime": {"end_time": "2025-11-25T15:04:58.459021Z", "start_time": "2025-11-25T15:04:58.457408Z"}}, "outputs": [], "source": ["# number of samples that are provided to the classifier\n", "init_train_length = 10\n", "# the size of the sliding window that limits the training data\n", "training_size = 3000\n", "# the parameter dedicated to decide if the classifier needs to be refited with X and y.\n", "fit_clf = False"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Random Seed Generation\n", "To make the experiments repeatable, we will use the `random_state` object to generate all other random seeds, such that we only need to explicitly specify a single random seed. The `get_randomseed` function simplifies the generation of a new random seed using the random_state object."]}, {"cell_type": "code", "execution_count": 4, "metadata": {"ExecuteTime": {"end_time": "2025-11-25T15:04:58.503282Z", "start_time": "2025-11-25T15:04:58.501416Z"}}, "outputs": [], "source": ["# random state that is used to generate random seeds\n", "random_state = np.random.RandomState(0)\n", "\n", "def get_randomseed(random_state):\n", " return random_state.randint(2**31-1)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Data Set\n", "The code loads the Reuters-21578 training split from Hugging Face and embeds all documents using a `SentenceTransformer`. The resulting embeddings are stored in `X`, while the corresponding class labels are stored in `y`. The distinct label set is extracted via `np.unique`. From these arrays, the first `init_train_length` samples form the initial training subset `(X_init, y_init)`, and the remaining samples define the data stream `(X_stream, y_stream)` processed during the active learning experiment."]}, {"cell_type": "code", "execution_count": 5, "metadata": {"ExecuteTime": {"end_time": "2025-11-25T15:05:06.172344Z", "start_time": "2025-11-25T15:04:58.545419Z"}}, "outputs": [], "source": ["# Load data from Huggingface and encode it via `sentence_transformers`.\n", "ds_train = load_dataset(\"yangwang825/reuters-21578\", split=\"train\")\n", "mdl = SentenceTransformer(\"all-MiniLM-L6-v2\", device=device)\n", "X = mdl.encode(ds_train[\"text\"])\n", "y = np.asarray(ds_train[\"label\"], dtype=np.int64)\n", "classes = np.unique(y)\n", "X_init = X[:init_train_length, :]\n", "y_init = y[:init_train_length]\n", "X_stream = X[init_train_length:, :]\n", "y_stream = y[init_train_length:]"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Classifier and Query Strategies\n", "The code defines factory functions so every run gets fresh objects instead of reusing stale state.\n", "- `clf_factory()` returns a new `ParzenWindowClassifier` with fixed hyperparameters and a randomized `random_state`.\n", "- `query_strategy_factories` maps strategy names to zero-argument lambdas, each creating a new instance of the corresponding query strategy with its own `random_state` (and extra args like `force_full_budget=True`).\n", "\n", "In the experiment loop you iterate over `query_strategy_factories.items()`, call `qs_factory()` to get a new query strategy, and then run the stream. This prevents leakage of internal state (budgets, counters, etc.) between runs and strategies."]}, {"cell_type": "code", "execution_count": 6, "metadata": {"ExecuteTime": {"end_time": "2025-11-25T15:05:06.221683Z", "start_time": "2025-11-25T15:05:06.219296Z"}}, "outputs": [], "source": ["def clf_factory():\n", " return ParzenWindowClassifier(\n", " classes=classes,\n", " random_state=get_randomseed(random_state),\n", " metric_dict={\"gamma\": \"mean\"},\n", " )\n", "\n", "\n", "query_strategy_factories = {\n", " \"StreamRandomSampling\": lambda: StreamRandomSampling(\n", " random_state=get_randomseed(random_state)\n", " ),\n", " \"PeriodicSampler\": lambda: PeriodicSampling(\n", " random_state=get_randomseed(random_state)\n", " ),\n", " # \"FixedUncertainty\": lambda: FixedUncertainty(\n", " # random_state=get_randomseed(random_state)\n", " # ),\n", " # \"VariableUncertainty\": lambda: VariableUncertainty(\n", " # random_state=get_randomseed(random_state)\n", " # ),\n", " \"Split\": lambda: Split(\n", " random_state=get_randomseed(random_state)\n", " ),\n", " \"DBALStream\": lambda: StreamDensityBasedAL(\n", " random_state=get_randomseed(random_state)\n", " ),\n", " # \"CogDQSRan\": lambda: CognitiveDualQueryStrategyRan(\n", " # random_state=get_randomseed(random_state),\n", " # force_full_budget=True,\n", " # ),\n", " # \"CogDQSFixUn\": lambda: CognitiveDualQueryStrategyFixUn(\n", " # random_state=get_randomseed(random_state),\n", " # force_full_budget=True,\n", " # ),\n", " # \"CogDQSVarUn\": lambda: CognitiveDualQueryStrategyVarUn(\n", " # random_state=get_randomseed(random_state),\n", " # force_full_budget=True,\n", " # ),\n", " \"CogDQSRanVarUn\": lambda: CognitiveDualQueryStrategyRanVarUn(\n", " random_state=get_randomseed(random_state),\n", " force_full_budget=True,\n", " ),\n", " \"StreamProbabilisticAL\": lambda: StreamProbabilisticAL(\n", " random_state=get_randomseed(random_state)\n", " ),\n", "}"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Active Learning Cycle\n", "Once all variables are initialized, we can start the experiment. The outer loop iterates over all query strategies stored in `query_strategies`. For each query strategy, we perform `n_repeats` independent runs. In each run, a fresh classifier is created, initialized with the same training window, and trained on the initial labeled data before it is exposed to the data stream. At every time step in the stream, the classifier is updated on the current training set, its prediction on the incoming instance is evaluated, and the query strategy decides whether the true label of that instance should be acquired. We record a Boolean indicating whether the prediction was correct as well as the number of acquired labels. After completing all time steps for a run, these sequences of correctness indicators and the total query count are stored. Finally, for each query strategy, all runs are collected in the `results` dictionary (containing the per-run correctness arrays and query counts), which can later be used to compute averages and to plot smoothed learning curves."]}, {"cell_type": "code", "execution_count": 7, "metadata": {"ExecuteTime": {"end_time": "2025-11-25T15:18:36.286771Z", "start_time": "2025-11-25T15:05:06.262507Z"}}, "outputs": [], "source": ["n_repeats = 5\n", "results = {}\n", "\n", "for query_strategy_name, query_strategy_factory in query_strategy_factories.items():\n", " all_correct_classifications = []\n", " all_counts = []\n", "\n", " for r in range(n_repeats):\n", " query_strategy = query_strategy_factory()\n", " clf = clf_factory()\n", "\n", " # initialize training data\n", " X_train = deque(maxlen=training_size)\n", " X_train.extend(X_init)\n", " y_train = deque(maxlen=training_size)\n", " y_train.extend(y_init)\n", "\n", " # initial training\n", " clf.fit(X_train, y_train)\n", "\n", " correct_classifications = []\n", " count = 0\n", "\n", " # if X_stream / y_stream are generators, make sure you materialize them\n", " # outside this loop; here we assume they are indexable / reusable\n", " for t, (x_t, y_t) in enumerate(zip(X_stream, y_stream)):\n", " X_cand = x_t.reshape(1, -1)\n", " y_cand = y_t\n", "\n", " # train classifier\n", " clf.fit(X_train, y_train)\n", "\n", " # prediction correctness\n", " correct_classifications.append(\n", " clf.predict(X_cand)[0] == y_cand\n", " )\n", "\n", " # query decision\n", " sampled_indices, utilities = call_func(\n", " query_strategy.query,\n", " candidates=X_cand,\n", " clf=clf,\n", " return_utilities=True,\n", " fit_clf=fit_clf,\n", " )\n", "\n", " budget_manager_param_dict = {\"utilities\": utilities}\n", "\n", " # update query strategy / budget manager\n", " call_func(\n", " query_strategy.update,\n", " candidates=X_cand,\n", " queried_indices=sampled_indices,\n", " budget_manager_param_dict=budget_manager_param_dict,\n", " )\n", "\n", " # count queries\n", " count += len(sampled_indices)\n", "\n", " # update training data\n", " X_train.append(x_t)\n", " y_train.append(y_cand if len(sampled_indices) > 0 else clf.missing_label)\n", "\n", " all_correct_classifications.append(correct_classifications)\n", " all_counts.append(count)\n", "\n", " # convert to arrays and store\n", " results[query_strategy_name] = {\n", " \"correct\": np.array(all_correct_classifications, dtype=float),\n", " \"counts\": np.array(all_counts, dtype=int),\n", " }"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Active Learning Results\n", "The plotting block takes the aggregated data in `results` and turns it into learning curves for each query strategy. For every entry in `results`, it first extracts the 2D array of correctness values, where each row corresponds to one repeat and each column to a time step in the stream. It then averages these correctness values across all repeats to obtain a mean accuracy curve over time. This mean curve is optionally smoothed using a Gaussian filter to reduce noise and make trends more visible.\n", "\n", "In addition, the code computes the overall average accuracy (as the mean of the mean curve) and the average number of acquired labels across repeats. These summary statistics are encoded directly in the legend label for each query strategy, so each curve is annotated with its mean performance and query usage."]}, {"cell_type": "code", "execution_count": 8, "metadata": {"ExecuteTime": {"end_time": "2025-11-25T15:19:21.342034Z", "start_time": "2025-11-25T15:19:21.107101Z"}}, "outputs": [{"data": {"image/png": 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", "text/plain": ["
"]}, "metadata": {}, "output_type": "display_data"}], "source": ["for query_strategy_name, res in results.items():\n", " correct = res[\"correct\"]\n", " mean_curve = correct.mean(axis=0)\n", " smoothed = gaussian_filter1d(mean_curve, 100)\n", "\n", " avg_acc = mean_curve.mean()\n", " avg_count = res[\"counts\"].mean()\n", "\n", " plt.plot(\n", " smoothed,\n", " label=f\"{query_strategy_name} (avg acc={avg_acc:.3f}, queries={avg_count:.1f})\",\n", " )\n", "\n", "plt.legend()\n", "plt.xlabel(\"Time step\")\n", "plt.ylabel(\"Accuracy (smoothed)\")\n", "plt.tight_layout()"]}], "metadata": {"kernelspec": {"display_name": "scikit-activeml", "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": "3.12.11"}, "nbsphinx": {"orphan": true}}, "nbformat": 4, "nbformat_minor": 4}