From ab7f3ca04b6c13c823eb069a726351e9638394a9 Mon Sep 17 00:00:00 2001 From: nikolay-bushkov Date: Fri, 21 Sep 2018 17:29:51 +0300 Subject: [PATCH] docs: refactor pool-based sampling example --- source/conf.py | 3 +- .../content/examples/Pool-based-sampling.rst | 78 --- .../examples/pool-based_sampling.ipynb | 396 +++++++++++++++ .../content/examples/ranked_batch_mode.ipynb | 452 ++++++++++++++++++ source/index.rst | 3 +- 5 files changed, 852 insertions(+), 80 deletions(-) delete mode 100644 source/content/examples/Pool-based-sampling.rst create mode 100644 source/content/examples/pool-based_sampling.ipynb create mode 100644 source/content/examples/ranked_batch_mode.ipynb diff --git a/source/conf.py b/source/conf.py index b8950dc..8f9a0b2 100644 --- a/source/conf.py +++ b/source/conf.py @@ -43,6 +43,7 @@ 'sphinx.ext.mathjax', 'sphinx.ext.viewcode', 'sphinx.ext.githubpages', + 'nbsphinx' ] # Add any paths that contain templates here, relative to this directory. @@ -67,7 +68,7 @@ # List of patterns, relative to source directory, that match files and # directories to ignore when looking for source files. # This pattern also affects html_static_path and html_extra_path . -exclude_patterns = [] +exclude_patterns = ['**.ipynb_checkpoints'] # The name of the Pygments (syntax highlighting) style to use. pygments_style = 'sphinx' diff --git a/source/content/examples/Pool-based-sampling.rst b/source/content/examples/Pool-based-sampling.rst deleted file mode 100644 index b82668b..0000000 --- a/source/content/examples/Pool-based-sampling.rst +++ /dev/null @@ -1,78 +0,0 @@ -Pool-based sampling -=================== - -One of the most well known settings for active learning is pool-based sampling. In this case, a pool of unlabelled instances are given to the active learner, which measures how well can it classify each example. Based upon this measurement, a utility score is generated. For instance, uncertain examples achieve high score and where the classification is certain, a low score is assigned. Labels are then requested for the most informative instances from an expert and these new labels are used to improve the model. In this example, this scenario is demonstrated on the famous iris dataset. - -The executable script for this example is `available here! `__ - -The dataset ------------ - -We are going to use the iris dataset for this example. For more information on the iris dataset, see `its wikipedia -page `__. For its scikit-learn interface, see `the scikit-learn -documentation `__. - -.. code:: python - - import numpy as np - from sklearn.decomposition import PCA - from sklearn.datasets import load_iris - - # loading the iris dataset - iris = load_iris() - - # initial training data - train_idx = [0, 50, 100] - X_training = iris['data'][train_idx] - y_training = iris['target'][train_idx] - - # generating the pool - X_pool = np.delete(iris['data'], train_idx, axis=0) - y_pool = np.delete(iris['target'], train_idx) - -If you perform a PCA on the iris dataset, here is how it looks like: - -.. figure:: img/pbs-iris_pca.png - :align: center - -Active learning ---------------- - -After the initial training data and the pool are generated, we are ready to do active learning! - -.. code:: python - - from modAL.models import ActiveLearner - from sklearn.neighbors import KNeighborsClassifier - - # initializing the active learner - learner = ActiveLearner( - estimator=KNeighborsClassifier(n_neighbors=3), - X_training=X_training, y_training=y_training - ) - -Before the active learning loop, here is how the predictions look like. - -.. figure:: img/pbs-initial.png - :align: center - -In this example, we will do 20 queries using maximum uncertainty sampling. - -.. code:: python - - # pool-based sampling - n_queries = 20 - for idx in range(n_queries): - query_idx, query_instance = learner.query(X_pool) - learner.teach( - X=X_pool[query_idx].reshape(1, -1), - y=y_pool[query_idx].reshape(1, ) - ) - # remove queried instance from pool - X_pool = np.delete(X_pool, query_idx, axis=0) - y_pool = np.delete(y_pool, query_idx) - -After the queries, the predicitions are much better: - -.. figure:: img/pbs-final.png - :align: center diff --git a/source/content/examples/pool-based_sampling.ipynb b/source/content/examples/pool-based_sampling.ipynb new file mode 100644 index 0000000..9d38306 --- /dev/null +++ b/source/content/examples/pool-based_sampling.ipynb @@ -0,0 +1,396 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Demo: Pool-based sampling\n", + "\n", + "## Overview\n", + "\n", + "In this example, the we apply an `ActiveLearner` onto the iris dataset using pool-based sampling. In this setting, we assume a small set of labeled data $\\mathcal{L}$ and a large set of unlabeled data $\\mathcal{U}$ such that $\\left| \\mathcal{L} \\right| \\ll \\left| \\mathcal{U} \\right|$. In his review of the active learning literature, Settles covers a high-level overview of the general pool-based sampling algorithm:\n", + "\n", + "> Queries are selectively drawn from the pool, which is usually assumed to be closed (i.e., static or non-changing), although this is not strictly necessary. Typically, instances are queried in a greedy fashion, according to an informativeness measure used to evaluate all instances in the pool (or, perhaps if $\\mathcal{U}$ is very large, some subsample thereof).\n", + "\n", + "Along with our pool-based sampling strategy, `modAL`'s modular design allows you to vary parameters surrounding the active learning process, including the core estimator and query strategy. In this example, we use `scikit-learn`'s [k-nearest neighbors classifier](http://scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsClassifier.html) as our estimator and default to `modAL`'s [uncertainty sampling](https://cosmic-cortex.github.io/modAL/Uncertainty-sampling) query strategy.\n", + "\n", + "For further reading on pool-based sampling, we highly recommend the following resources:\n", + "- Burr Settles. [Active Learning Literature Survey](http://burrsettles.com/pub/settles.activelearning.pdf) [**Section 2.3: Pool-based Sampling**]. Computer Sciences Technical Report 1648, University of Wisconsin-Madison. 2009." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Enforce a reproducible result across runs" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "\n", + "# Set our RNG seed for reproducibility.\n", + "RANDOM_STATE_SEED = 123\n", + "np.random.seed(RANDOM_STATE_SEED)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Load our `iris` dataset\n", + "\n", + "For more information on the iris dataset, see:\n", + " - [The dataset documentation on Wikipedia](https://en.wikipedia.org/wiki/Iris_flower_data_set)\n", + " - [The scikit-learn interface](http://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_iris.html)" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.datasets import load_iris\n", + "\n", + "iris = load_iris()\n", + "X_raw = iris['data'] \n", + "y_raw = iris['target']" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Apply PCA onto our features and extract the first 2 principle components" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.decomposition import PCA\n", + "\n", + "# Define our PCA transformer and fit it onto our raw dataset.\n", + "pca = PCA(n_components=2, random_state=RANDOM_STATE_SEED)\n", + "transformed_iris = pca.fit_transform(X=X_raw)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Visualize the principle components" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "%matplotlib inline\n", + "import matplotlib as mpl\n", + "import matplotlib.pyplot as plt\n", + "\n", + "# Isolate the data we'll need for plotting.\n", + "x_component, y_component = transformed_iris[:, 0], transformed_iris[:, 1]\n", + "\n", + "# Plot our dimensionality-reduced (via PCA) dataset.\n", + "plt.figure(figsize=(8.5, 6), dpi=130)\n", + "plt.scatter(x=x_component, y=y_component, c=y_raw, cmap='viridis', s=50, alpha=8/10)\n", + "plt.title('Iris classes after PCA transformation')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Partition our `iris` dataset\n", + "\n", + "We first specify our training set $\\mathcal{L}$ consisting of 3 random examples. The remaining examples go to our \"unlabeled\" pool $\\mathcal{U}$." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "# Isolate our examples for our labeled dataset.\n", + "n_labeled_examples = X_raw.shape[0]\n", + "training_indices = np.random.randint(low=0, high=n_labeled_examples + 1, size=3)\n", + "\n", + "X_train = X_raw[training_indices]\n", + "y_train = y_raw[training_indices]\n", + "\n", + "# Isolate the non-training examples we'll be querying.\n", + "X_pool = np.delete(X_raw, training_indices, axis=0)\n", + "y_pool = np.delete(y_raw, training_indices, axis=0)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Define our models" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.neighbors import KNeighborsClassifier\n", + "from modAL.models import ActiveLearner\n", + "\n", + "# Specify our core estimator along with it's active learning model.\n", + "knn = KNeighborsClassifier(n_neighbors=3)\n", + "learner = ActiveLearner(estimator=knn, X_training=X_train, y_training=y_train)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Predict class labels based on our limited dataset $\\mathcal{L}$" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n", + " 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n", + " 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n", + " 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n", + " 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n", + " 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n", + " 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2])" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Isolate the data we'll need for plotting.\n", + "predictions = learner.predict(X_raw)\n", + "is_correct = (predictions == y_raw)\n", + "\n", + "predictions" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Record our learner's score on the raw data.\n", + "unqueried_score = learner.score(X_raw, y_raw)\n", + "\n", + "# Plot our classification results.\n", + "fig, ax = plt.subplots(figsize=(8.5, 6), dpi=130)\n", + "ax.scatter(x=x_component[is_correct], y=y_component[is_correct], c='g', marker='+', label='Correct', alpha=8/10)\n", + "ax.scatter(x=x_component[~is_correct], y=y_component[~is_correct], c='r', marker='x', label='Incorrect', alpha=8/10)\n", + "ax.legend(loc='lower right')\n", + "ax.set_title(\"ActiveLearner class predictions (Accuracy: {score:.3f})\".format(score=unqueried_score))\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Update our model by pool-based sampling our \"unlabeled\" dataset $\\mathcal{U}$\n", + "\n", + "As we can see, our model is unable to properly learn the underlying data distribution. All of its predictions are for the third class label, and as such it is only as competitive as defaulting its predictions to a single class – if only we had more data!\n", + "\n", + "Below, we tune our classifier by allowing it to query 20 instances it hasn't seen before. Using uncertainty sampling, our classifier aims to reduce the amount of uncertainty in its predictions using a variety of measures — see the documentation for more on specific [classification uncertainty measures](https://cosmic-cortex.github.io/modAL/Uncertainty-sampling#uncertainty). With each requested query, we remove that record from our pool $\\mathcal{U}$ and record our model's accuracy on the raw dataset." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy after query 1: 0.6667\n", + "Accuracy after query 2: 0.6667\n", + "Accuracy after query 3: 0.8800\n", + "Accuracy after query 4: 0.8800\n", + "Accuracy after query 5: 0.8733\n", + "Accuracy after query 6: 0.8400\n", + "Accuracy after query 7: 0.7400\n", + "Accuracy after query 8: 0.7267\n", + "Accuracy after query 9: 0.7267\n", + "Accuracy after query 10: 0.7267\n", + "Accuracy after query 11: 0.7267\n", + "Accuracy after query 12: 0.7267\n", + "Accuracy after query 13: 0.7267\n", + "Accuracy after query 14: 0.7267\n", + "Accuracy after query 15: 0.7200\n", + "Accuracy after query 16: 0.8400\n", + "Accuracy after query 17: 0.8800\n", + "Accuracy after query 18: 0.8933\n", + "Accuracy after query 19: 0.9267\n", + "Accuracy after query 20: 0.9267\n" + ] + } + ], + "source": [ + "N_QUERIES = 20\n", + "performance_history = [unqueried_score]\n", + "\n", + "# Allow our model to query our unlabeled dataset for the most\n", + "# informative points according to our query strategy (uncertainty sampling).\n", + "for index in range(N_QUERIES):\n", + " query_index, query_instance = learner.query(X_pool)\n", + " \n", + " # Teach our ActiveLearner model the record it has requested.\n", + " X, y = X_pool[query_index].reshape(1, -1), y_pool[query_index].reshape(1, )\n", + " learner.teach(X=X, y=y)\n", + " \n", + " # Remove the queried instance from the unlabeled pool.\n", + " X_pool, y_pool = np.delete(X_pool, query_index, axis=0), np.delete(y_pool, query_index)\n", + " \n", + " # Calculate and report our model's accuracy.\n", + " model_accuracy = learner.score(X_raw, y_raw)\n", + " print('Accuracy after query {n}: {acc:0.4f}'.format(n=index + 1, acc=model_accuracy))\n", + " \n", + " # Save our model's performance for plotting.\n", + " performance_history.append(model_accuracy)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Plot our performance over time.\n", + "fig, ax = plt.subplots(figsize=(8.5, 6), dpi=130)\n", + "\n", + "ax.plot(performance_history)\n", + "ax.scatter(range(len(performance_history)), performance_history, s=13)\n", + "\n", + "ax.xaxis.set_major_locator(mpl.ticker.MaxNLocator(nbins=5, integer=True))\n", + "ax.yaxis.set_major_locator(mpl.ticker.MaxNLocator(nbins=10))\n", + "ax.yaxis.set_major_formatter(mpl.ticker.PercentFormatter(xmax=1))\n", + "\n", + "ax.set_ylim(bottom=0, top=1)\n", + "ax.grid(True)\n", + "\n", + "ax.set_title('Incremental classification accuracy')\n", + "ax.set_xlabel('Query iteration')\n", + "ax.set_ylabel('Classification Accuracy')\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Isolate the data we'll need for plotting.\n", + "predictions = learner.predict(X_raw)\n", + "is_correct = (predictions == y_raw)\n", + "\n", + "# Plot our updated classification results once we've trained our learner.\n", + "fig, ax = plt.subplots(figsize=(8.5, 6), dpi=130)\n", + "\n", + "ax.scatter(x=x_component[is_correct], y=y_component[is_correct], c='g', marker='+', label='Correct', alpha=8/10)\n", + "ax.scatter(x=x_component[~is_correct], y=y_component[~is_correct], c='r', marker='x', label='Incorrect', alpha=8/10)\n", + "\n", + "ax.set_title('Classification accuracy after {n} queries: {final_acc:.3f}'.format(n=N_QUERIES, final_acc=performance_history[-1]))\n", + "ax.legend(loc='lower right')\n", + "\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "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": "3.6.6" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/source/content/examples/ranked_batch_mode.ipynb b/source/content/examples/ranked_batch_mode.ipynb new file mode 100644 index 0000000..fe193d6 --- /dev/null +++ b/source/content/examples/ranked_batch_mode.ipynb @@ -0,0 +1,452 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Demo: Ranked batch-mode sampling\n", + "\n", + "## Overview\n", + "\n", + "In this example, we apply an `ActiveLearner` onto the iris dataset using **ranked batch-mode active learning**. Much like pool-based sampling, in this setting we assume a small (potentially empty) set of labeled data $\\mathcal{L}$ and a large set of unlabeled data $\\mathcal{U}$ such that $\\left| \\mathcal{L} \\right| \\ll \\left| \\mathcal{U} \\right|$.\n", + "\n", + "One of the drawbacks of standard pool-based sampling (indeed, most sampling techniques) is their interactive nature: these sampling methods are best fit for cases where we have an attentive human-in-the-loop for maximizing the model's performance. Although these sampling methods (ours included!) _do_ support returning multiple samples per query, they tend to return redundant/sub-optimal queries if we return more than one instance from the unlabeled set. This is a bit prohibitive in settings where we'd like to ask an active learner to return multiple (if not all) examples from the unlabeled set/pool.\n", + "\n", + "This implementation (see the original issue [here](https://github.com/cosmic-cortex/modAL/issues/11)) implements Cardoso et al.'s **ranked batch-mode** sampling, which not only supports batch-mode sampling (sampling methods that are built with querying multiple labels from the unlabeled set) but also establishes a _ranking_ among the batch in order for end-users to prioritize which records to label from the unlabeled set. In their own words:\n", + "\n", + "> Our new approach allows the algorithm to generate an arbitrarily long query, thus making its execution less frequent. For example, a ranked query containing every available instance could be generated outside working hours. This would allow hired analysts to label instances for a full day, in parallel, if desired, without waiting for the learner update and query reconstruction.\n", + "\n", + "For further reading on ranked batch-mode active learning, we highly recommend the following resources:\n", + "\n", + "- Thiago N.C. Cardoso, Rodrigo M. Silva, Sérgio Canuto, Mirella M. Moro, Marcos A. Gonçalves. [Ranked batch-mode active learning](http://www.sciencedirect.com/science/article/pii/S0020025516313949). Information Sciences, Volume 379, 2017, Pages 313-337.\n", + "\n", + "## Note\n", + "\n", + "Although this notebook only highlights the benefits of batch sampling (as opposed to interactive sampling), the same ideas hold for ranked batch-mode sampling. One day we'll get around to producing examples where ranked batch-mode sampling is the core idea being evaluated :)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Enforce a reproducible result across runs" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "\n", + "# Set our RNG for reproducibility.\n", + "RANDOM_STATE_SEED = 123\n", + "np.random.seed(RANDOM_STATE_SEED)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Load our `iris` dataset" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/danny/miniconda3/envs/ac3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88\n", + " return f(*args, **kwds)\n", + "/Users/danny/miniconda3/envs/ac3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88\n", + " return f(*args, **kwds)\n", + "/Users/danny/miniconda3/envs/ac3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88\n", + " return f(*args, **kwds)\n", + "/Users/danny/miniconda3/envs/ac3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88\n", + " return f(*args, **kwds)\n" + ] + } + ], + "source": [ + "from sklearn.datasets import load_iris\n", + "\n", + "iris = load_iris()\n", + "X_raw = iris['data'] \n", + "y_raw = iris['target']" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Apply PCA onto our features and extract the first 2 principle components" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/danny/miniconda3/envs/ac3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88\n", + " return f(*args, **kwds)\n" + ] + } + ], + "source": [ + "from sklearn.decomposition import PCA\n", + "\n", + "# Define our PCA transformer and fit it onto our raw dataset.\n", + "pca = PCA(n_components=2, random_state=RANDOM_STATE_SEED)\n", + "transformed_iris = pca.fit_transform(X=X_raw)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Visualize the principle components" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "%matplotlib inline\n", + "import matplotlib as mpl\n", + "import matplotlib.pyplot as plt\n", + "\n", + "# Isolate the data we'll need for plotting.\n", + "x_component, y_component = transformed_iris[:, 0], transformed_iris[:, 1]\n", + "\n", + "# Plot our dimensionality-reduced (via PCA) dataset.\n", + "plt.figure(figsize=(8.5, 6), dpi=130)\n", + "plt.scatter(x=x_component, y=y_component, c=y_raw, cmap='viridis', s=50, alpha=8/10)\n", + "plt.title('Iris classes after PCA transformation')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Partition our `iris` dataset into $\\mathcal{L}$ and $\\mathcal{U}$\n", + "\n", + "We first specify our training set $\\mathcal{L}$ consisting of 3 random examples. The remaining examples go to our \"unlabeled\" pool $\\mathcal{U}$." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "# Isolate our examples for our labeled dataset.\n", + "n_labeled_examples = X_raw.shape[0]\n", + "training_indices = np.random.randint(low=0, high=n_labeled_examples + 1, size=3)\n", + "\n", + "X_train = X_raw[training_indices]\n", + "y_train = y_raw[training_indices]\n", + "\n", + "# Isolate the non-training examples we'll be querying.\n", + "X_pool = np.delete(X_raw, training_indices, axis=0)\n", + "y_pool = np.delete(y_raw, training_indices, axis=0)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Define our core estimator and active learning models" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.neighbors import KNeighborsClassifier\n", + "\n", + "# Specify our core estimator.\n", + "knn = KNeighborsClassifier(n_neighbors=3)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "from functools import partial\n", + "from modAL.batch import uncertainty_batch_sampling\n", + "from modAL.models import ActiveLearner\n", + "\n", + "# Pre-set our batch sampling to retrieve 3 samples at a time.\n", + "BATCH_SIZE = 3\n", + "preset_batch = partial(uncertainty_batch_sampling, n_instances=BATCH_SIZE)\n", + "\n", + "# Specify our active learning model.\n", + "learner = ActiveLearner(\n", + " estimator=knn, \n", + " \n", + " X_training=X_train,\n", + " y_training=y_train, \n", + " \n", + " query_strategy=preset_batch\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Predict class labels based on our limited dataset $\\mathcal{L}$" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n", + " 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n", + " 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n", + " 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n", + " 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n", + " 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,\n", + " 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2])" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Isolate the data we'll need for plotting.\n", + "predictions = learner.predict(X_raw)\n", + "is_correct = (predictions == y_raw)\n", + "\n", + "predictions" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Record our learner's score on the raw data.\n", + "unqueried_score = learner.score(X_raw, y_raw)\n", + "\n", + "# Plot our classification results.\n", + "fig, ax = plt.subplots(figsize=(8.5, 6), dpi=130)\n", + "ax.scatter(x=x_component[is_correct], y=y_component[is_correct], c='g', marker='+', label='Correct')\n", + "ax.scatter(x=x_component[~is_correct], y=y_component[~is_correct], c='r', marker='x', label='Incorrect')\n", + "ax.legend(loc='lower right')\n", + "ax.set_title(\"ActiveLearner class predictions (Accuracy: {score:.3f})\".format(score=unqueried_score))\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Update our model by batch-mode sampling our \"unlabeled\" dataset $\\mathcal{U}$\n", + "\n", + "We tune our classifier by allowing it to query at most 20 instances it hasn't seen before. To properly utilize batch-mode sampling, we allow our model to request three records per query (instead of 1) but subsequently only allow our model to make 6 queries. Under the hood, our classifier aims to balance the ideas behind uncertainty and dissimilarity in its choices.\n", + "\n", + "With each requested query, we remove that record from our pool $\\mathcal{U}$ and record our model's accuracy on the raw dataset." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy after query 1: 0.8733\n", + "Accuracy after query 2: 0.9333\n", + "Accuracy after query 3: 0.9333\n", + "Accuracy after query 4: 0.9467\n", + "Accuracy after query 5: 0.9733\n", + "Accuracy after query 6: 0.9667\n" + ] + } + ], + "source": [ + "# Pool-based sampling\n", + "N_RAW_SAMPLES = 20\n", + "N_QUERIES = N_RAW_SAMPLES // BATCH_SIZE\n", + "\n", + "performance_history = [unqueried_score]\n", + "\n", + "for index in range(N_QUERIES):\n", + " query_index, query_instance = learner.query(X_pool)\n", + " \n", + " # Teach our ActiveLearner model the record it has requested.\n", + " X, y = X_pool[query_index], y_pool[query_index]\n", + " learner.teach(X=X, y=y)\n", + " \n", + " # Remove the queried instance from the unlabeled pool.\n", + " X_pool = np.delete(X_pool, query_index, axis=0)\n", + " y_pool = np.delete(y_pool, query_index)\n", + " \n", + " # Calculate and report our model's accuracy.\n", + " model_accuracy = learner.score(X_raw, y_raw)\n", + " print('Accuracy after query {n}: {acc:0.4f}'.format(n=index + 1, acc=model_accuracy))\n", + " \n", + " # Save our model's performance for plotting.\n", + " performance_history.append(model_accuracy)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Evaluate our model's performance\n", + "\n", + "Here, we first plot the query iteration index against model accuracy. As you can see, our model is able to obtain an accuracy of ~0.90 within its first query, and isn't as susceptible to getting \"stuck\" with querying uninformative records from our unlabeled set $\\mathcal{U}$." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib as mpl\n", + "import matplotlib.pyplot as plt\n", + "\n", + "# Plot our performance over time.\n", + "fig, ax = plt.subplots(figsize=(8.5, 6), dpi=130)\n", + "\n", + "ax.plot(performance_history)\n", + "ax.scatter(range(len(performance_history)), performance_history, s=13)\n", + "\n", + "ax.xaxis.set_major_locator(mpl.ticker.MaxNLocator(nbins=N_QUERIES + 3, integer=True))\n", + "ax.xaxis.grid(True)\n", + "\n", + "ax.yaxis.set_major_locator(mpl.ticker.MaxNLocator(nbins=10))\n", + "ax.yaxis.set_major_formatter(mpl.ticker.PercentFormatter(xmax=1))\n", + "ax.set_ylim(bottom=0, top=1)\n", + "ax.yaxis.grid(True, linestyle='--', alpha=1/2)\n", + "\n", + "ax.set_title('Incremental classification accuracy')\n", + "ax.set_xlabel('Query iteration')\n", + "ax.set_ylabel('Classification Accuracy')\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Isolate the data we'll need for plotting.\n", + "predictions = learner.predict(X_raw)\n", + "is_correct = (predictions == y_raw)\n", + "\n", + "# Plot our updated classification results once we've trained our learner.\n", + "fig, ax = plt.subplots(figsize=(8.5, 6), dpi=130)\n", + "\n", + "ax.scatter(x=x_component[is_correct], y=y_component[is_correct], c='g', marker='+', label='Correct')\n", + "ax.scatter(x=x_component[~is_correct], y=y_component[~is_correct], c='r', marker='x', label='Incorrect')\n", + "\n", + "ax.set_title('Classification accuracy after {n} queries (* {batch_size} samples/query = {total} samples): {final_acc:.3f}'.format(\n", + " n=N_QUERIES, \n", + " batch_size=BATCH_SIZE,\n", + " total=N_QUERIES * BATCH_SIZE,\n", + " final_acc=performance_history[-1]\n", + "))\n", + "ax.legend(loc='lower right')\n", + "\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "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": "3.6.6" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/source/index.rst b/source/index.rst index a0e9a48..87dd0d9 100644 --- a/source/index.rst +++ b/source/index.rst @@ -233,7 +233,8 @@ Danka `__ (aka :maxdepth: 1 :caption: Examples - Pool-based sampling + Pool-based sampling + Ranked batch-mode sampling Stream-based sampling Active regression Ensemble regression