From 65299f5280c433d719960eb2b5e8b6b3b6b54906 Mon Sep 17 00:00:00 2001 From: bbayukari <17bbayukari@gmail.com> Date: Tue, 18 Jun 2024 20:06:29 +0800 Subject: [PATCH] doc: fix bugs in doc --- docs/source/feature/DataScienceTool.rst | 4 +- docs/source/feature/Variants.rst | 6 +- .../gamma-regression.ipynb | 113 +-------- .../gallery/GeneralizedLinearModels/index.rst | 1 + .../logistic-regression.ipynb | 211 +++++----------- .../quantile-expectile-regression.ipynb | 38 ++- docs/source/userguide/install.rst | 11 - docs/source/userguide/quickstart.rst | 2 +- docs/source/userguide/whatscope.rst | 12 +- skscope/utilities.py | 228 +++++++++++++++--- 10 files changed, 297 insertions(+), 329 deletions(-) diff --git a/docs/source/feature/DataScienceTool.rst b/docs/source/feature/DataScienceTool.rst index 3e6b66d..b5cdd1a 100644 --- a/docs/source/feature/DataScienceTool.rst +++ b/docs/source/feature/DataScienceTool.rst @@ -79,9 +79,9 @@ Information Criterion Information criterion is a statistical measure used to assess the goodness of fit of a model while penalizing model complexity. It helps in selecting the optimal model from a set of competing models. In the context of sparsity-constrained optimization, information criterion can be used to evaluate different sparsity levels and identify the most suitable support size. -.. There is another way to evaluate sparsity levels, which is information criterion. The smaller the information criterion, the better the model. +There is another way to evaluate sparsity levels, which is information criterion. The smaller the information criterion, the better the model. There are four types of information criterion can be implemented in ``skscope.utilities``: Akaike information criterion `[1]`_, Bayesian information criterion (BIC, `[2]`_), extend BIC `[3]`_, and special information criterion (SIC `[4]`_). -.. If sparsity is list and ``cv=None``, the solver will use information criterions to evaluate the sparsity level. +If sparsity is list and ``cv=None``, the solver will use information criterions to evaluate the sparsity level. The input parameter ``ic_method`` in the solvers of skscope can be used to choose the information criterion. It should be a method to compute information criterion which has the same parameters with this example: .. code-block:: python diff --git a/docs/source/feature/Variants.rst b/docs/source/feature/Variants.rst index 2786abc..e8b4151 100644 --- a/docs/source/feature/Variants.rst +++ b/docs/source/feature/Variants.rst @@ -8,7 +8,7 @@ In addition to standard sparsity-constrained optimization (SCO) problems, ``sksc Group-structured parameters ---------------------------- -In certain cases, we may encounter group-structured parameters where all parameters are divided into non-overlapping groups. Examples of such scenarios include group variable selection under linear model `[1]`_, `multitask learning <../userguide/examples/GeneralizedLinearModels/multiple-response-linear-regression.html>`__, and so on. +In certain cases, we may encounter group-structured parameters where all parameters are divided into non-overlapping groups. Examples of such scenarios include group variable selection under linear model `[1]`_, `multitask learning <../gallery/GeneralizedLinearModels/multiple-response-linear-regression.html>`__, and so on. When dealing with group-structured parameters, we treat each parameter group as a unit, selecting or deselecting all the parameters in the group simultaneously. This problem is referred to as group SCO (GSCO). @@ -174,8 +174,8 @@ In some cases, there may be additional constraints on the intrinsic structure of .. math:: \arg\min_{\theta \in R^s, \theta \in \mathcal{C}} f(\theta). - -A typical example is the Gaussian graphical model for continuous random variables, which constrains :math:`\theta` on symmetric positive-definite spaces (see this example `<../userguide/examples/GraphicalModels/sparse-gaussian-precision-matrix.html>`__). Although the default numeric solver cannot solve this problem, ``skscope`` provides a flexible interface that allows for its replacement. Specifically, users can change the default numerical optimization solver by properly setting the ``numeric_solver`` in the solver. + +A typical example is the Gaussian graphical model for continuous random variables, which constrains :math:`\theta` on symmetric positive-definite spaces (see this example `gaussian precision matrix <../gallery/GraphicalModels/sparse-gaussian-precision-matrix.html>`__). Although the default numeric solver cannot solve this problem, ``skscope`` provides a flexible interface that allows for its replacement. Specifically, users can change the default numerical optimization solver by properly setting the ``numeric_solver`` in the solver. > Notice that, the accepted input of ``numeric_solver`` should have the same interface as ``skscope.numeric_solver.convex_solver_LBFGS``. diff --git a/docs/source/gallery/GeneralizedLinearModels/gamma-regression.ipynb b/docs/source/gallery/GeneralizedLinearModels/gamma-regression.ipynb index b17c6f9..9b437f0 100644 --- a/docs/source/gallery/GeneralizedLinearModels/gamma-regression.ipynb +++ b/docs/source/gallery/GeneralizedLinearModels/gamma-regression.ipynb @@ -317,110 +317,7 @@ "id": "c4d3720f", "metadata": {}, "source": [ - "Now the `solver.params` contains the coefficients of gamma model with no more than 5 variables. That is, those variables with a coefficient 0 is unused in the model:" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "e416367f", - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[10.96270773 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 1.2021258 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0.99600871 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 1.74258709 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 1.18841825 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 1.46535362 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. ]\n" - ] - } - ], - "source": [ - "print(solver.params)" + "Now the `solver.params` contains the coefficients of gamma model with no more than 5 variables." ] }, { @@ -557,14 +454,6 @@ "- [2] Abess docs, \"make_glm_data\".\n", "https://abess.readthedocs.io/en/latest/Python-package/datasets/glm.html\n" ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "84ae9a94", - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { diff --git a/docs/source/gallery/GeneralizedLinearModels/index.rst b/docs/source/gallery/GeneralizedLinearModels/index.rst index 8ff806f..a5cfad4 100644 --- a/docs/source/gallery/GeneralizedLinearModels/index.rst +++ b/docs/source/gallery/GeneralizedLinearModels/index.rst @@ -12,4 +12,5 @@ Generalized Linear Models gamma-regression multiple-response-linear-regression multinomial-logistic-regression + poisson-identity-link .. Inverse-gaussian-regression diff --git a/docs/source/gallery/GeneralizedLinearModels/logistic-regression.ipynb b/docs/source/gallery/GeneralizedLinearModels/logistic-regression.ipynb index f838e53..b067b3a 100644 --- a/docs/source/gallery/GeneralizedLinearModels/logistic-regression.ipynb +++ b/docs/source/gallery/GeneralizedLinearModels/logistic-regression.ipynb @@ -6,10 +6,10 @@ "metadata": {}, "source": [ "\n", - "# Logistic Regressions\n", + "## Logistic Regressions\n", "------------\n", "\n", - "## Part A, we would like to use an example to show how the sparse-constrained optimization for logistic regression works in our program." + "### Part A, we would like to use an example to show how the sparse-constrained optimization for logistic regression works in our program." ] }, { @@ -46,7 +46,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 1, "id": "4020f0a5", "metadata": {}, "outputs": [], @@ -57,24 +57,6 @@ "import numpy as np" ] }, - { - "cell_type": "markdown", - "id": "ec16df9f", - "metadata": {}, - "source": [ - "### Set a seed" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "b49ef6ca", - "metadata": {}, - "outputs": [], - "source": [ - "np.random.seed(123)" - ] - }, { "cell_type": "markdown", "id": "8e3318e9", @@ -87,15 +69,15 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 12, "id": "dd0d0594", "metadata": {}, "outputs": [], "source": [ - "def data_generator(n, p, k, seed):\n", + "def make_logistic_data(n, p, k, seed):\n", " coef = np.zeros(p)\n", " np.random.seed(seed)\n", - " coef[np.random.choice(np.arange(p), k, replace=False)] = np.random.choice([1, -1], k) * 100\n", + " coef[np.random.choice(np.arange(p), k, replace=False)] = np.random.choice([1, -1], k)\n", " # generate correlation matrix with exponential decay\n", " R = np.zeros((p, p))\n", " for i in range(p):\n", @@ -125,13 +107,13 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 13, "id": "da82b90a", "metadata": {}, "outputs": [], "source": [ - "n, p, s, rho = 500, 500, 5, 0.0\n", - "X, y, true_params, true_support_set = make_logistic_data(n, p, s, rho , 0)" + "n, p, s = 500, 500, 5\n", + "true_params, (X, y) = make_logistic_data(n, p, s, 0)" ] }, { @@ -146,14 +128,14 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 14, "id": "29c7bf03", "metadata": {}, "outputs": [], "source": [ "def logistic_loss(params):\n", - " xbeta = jnp.clip(X @ params, -30, 30)\n", - " return jnp.sum(jnp.log(1 + jnp.exp(xbeta)) - y * xbeta)" + " xbeta = X @ params\n", + " return jnp.sum(jnp.logaddexp(0, xbeta) - y * xbeta)" ] }, { @@ -174,45 +156,16 @@ }, { "cell_type": "code", - "execution_count": 19, - "id": "adee6411", - "metadata": {}, - "outputs": [], - "source": [ - "from skscope.utilities import SIC" - ] - }, - { - "cell_type": "code", - "execution_count": 20, + "execution_count": 17, "id": "3f8fb0dd", "metadata": {}, "outputs": [], "source": [ - "solver = ScopeSolver(p, sparsity = range(1,10), sample_size = n, ic_method = SIC)\n", + "from skscope.utilities import SIC\n", + "solver = ScopeSolver(p, sparsity = range(10), sample_size = n, ic_method = SIC)\n", "params = solver.solve(logistic_loss, jit=True)" ] }, - { - "cell_type": "code", - "execution_count": 8, - "id": "4472f505", - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[1.2883844 1.25061865 1.80887014 1.11882953 1.4487943 ]\n" - ] - } - ], - "source": [ - "print(solver.params[solver.get_support()])" - ] - }, { "cell_type": "markdown", "id": "7352ee5e", @@ -229,7 +182,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 21, "id": "6b080ad7", "metadata": {}, "outputs": [ @@ -237,53 +190,20 @@ "name": "stdout", "output_type": "stream", "text": [ - "True support set: (array([ 90, 97, 340, 395, 477]),)\n", - "Estimated support set: [ 90 97 340 395 477]\n" - ] - } - ], - "source": [ - "print(\"True support set: \", (true_params.nonzero()))\n", - "print(\"Estimated support set: \", (solver.support_set))" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "id": "35c717e8", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "True parameters: [ 100. -100. 100. -100. -100.]\n", - "Estimated parameters: [ 4398.05269919 -4284.12650116 4302.04134409 -4283.66682006\n", - " -4274.74040784]\n" + "True support set: [ 90 97 340 395 477]\n", + "Estimated support set: [ 90 97 340 395 477]\n", + "True parameters: [ 1. -1. 1. -1. -1.]\n", + "Estimated parameters: [ 1.30554097 -1.04517175 1.05883086 -1.25463866 -1.17597009]\n", + "True loss value: 200.56027\n", + "Estimated loss value: 197.75107\n" ] } ], "source": [ + "print(\"True support set: \", (true_params.nonzero()[0]))\n", + "print(\"Estimated support set: \", (solver.support_set))\n", "print(\"True parameters: \", true_params[true_params.nonzero()])\n", - "print(\"Estimated parameters: \", solver.params[solver.support_set])" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "id": "5ec381f6", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "True loss value: 3.9117422\n", - "Estimated loss value: 1.4066623e-05\n" - ] - } - ], - "source": [ + "print(\"Estimated parameters: \", solver.params[solver.support_set])\n", "print(\"True loss value: \", logistic_loss(true_params))\n", "print(\"Estimated loss value: \", logistic_loss(solver.params))" ] @@ -300,13 +220,13 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 22, "id": "95bab082", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", "text/plain": [ "
" ] @@ -345,7 +265,7 @@ "id": "40afeb7f", "metadata": {}, "source": [ - "## Part B, we will use cross-validation to select the optimal support set and compare its runtime with that of SIC." + "### Part B, we will use cross-validation to select the optimal support set and compare its runtime with that of SIC." ] }, { @@ -358,7 +278,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 25, "id": "67358a0b", "metadata": {}, "outputs": [ @@ -366,9 +286,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "True support set: (array([ 90, 97, 340, 395, 477]),)\n", + "True support set: [ 90 97 340 395 477]\n", "skscope estimated support set: [ 90 97 340 395 477]\n", - "Runtime of SIC: 0.4018411636352539 seconds\n" + "Runtime of SIC: 0.7247357368469238 seconds\n" ] } ], @@ -377,11 +297,11 @@ "# Record start time\n", "start_time = time.time()\n", "\n", - "solver_ic = ScopeSolver(p, sparsity = range(1, 10), sample_size = n, ic_method = SIC)\n", + "solver_ic = ScopeSolver(p, sparsity = range(10), sample_size = n, ic_method = SIC)\n", "params_ic = solver_ic.solve(logistic_loss, jit=True)\n", "\n", "# Variable selection accuracy\n", - "print(\"True support set: \", (true_params.nonzero()))\n", + "print(\"True support set: \", (true_params.nonzero()[0]))\n", "print(\"skscope estimated support set: \", (solver_ic.support_set))\n", "\n", "# Calculate runtime\n", @@ -399,7 +319,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 26, "id": "88011386", "metadata": {}, "outputs": [ @@ -407,26 +327,27 @@ "name": "stdout", "output_type": "stream", "text": [ - "True support set: (array([ 90, 97, 340, 395, 477]),)\n", + "True support set: [ 90 97 340 395 477]\n", "skscope estimated support set: [ 90 97 340 395 477]\n", - "Runtime of CV: 3.7037763595581055 seconds\n" + "Runtime of CV: 4.354445219039917 seconds\n" ] } ], "source": [ "def logistic_loss_cv(params, data):\n", - " xbeta = jnp.clip(data[0] @ params, -30, 30)\n", - " return jnp.sum(jnp.log(1 + jnp.exp(xbeta)) - data[1] * xbeta)\n", + " X, y = data\n", + " xbeta = X @ params\n", + " return jnp.sum(jnp.logaddexp(0, xbeta) - y * xbeta)\n", "\n", "# Record start time\n", "start_time = time.time()\n", "\n", - "solver_cv = ScopeSolver(p, sparsity = range(1, 10), sample_size = n, cv = 5,\n", + "solver_cv = ScopeSolver(p, sparsity = range(10), sample_size = n, cv = 5,\n", " split_method=lambda data, index: (data[0][index, :], data[1][index]))\n", "params_cv = solver_cv.solve(logistic_loss_cv, jit=True, data=(X, y))\n", "\n", "# Variable selection accuracy\n", - "print(\"True support set: \", (true_params.nonzero()))\n", + "print(\"True support set: \", (true_params.nonzero()[0]))\n", "print(\"skscope estimated support set: \", (solver_cv.support_set))\n", "\n", "# Calculate runtime\n", @@ -447,7 +368,7 @@ "id": "1f36004a", "metadata": {}, "source": [ - "## Part C, we compare the results under two different circumstances: using warmstart and not using warmstart." + "### Part C, we compare the results under two different circumstances: using warmstart and not using warmstart." ] }, { @@ -458,9 +379,17 @@ "#### Using warmstart " ] }, + { + "cell_type": "markdown", + "id": "f33fac23", + "metadata": {}, + "source": [ + "Hint: all solvers default to using warmstart, which can slightly prolong computation time if not utilized" + ] + }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 29, "id": "be3ae766", "metadata": {}, "outputs": [ @@ -468,7 +397,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Runtime: 0.24225878715515137 seconds\n" + "Runtime: 4.619333982467651 seconds\n" ] } ], @@ -476,8 +405,9 @@ "# Record start time\n", "start_time = time.time()\n", "\n", - "solver_ws = ScopeSolver(p, s)\n", - "params_ws = solver_ws.solve(logistic_loss, jit=True)\n", + "solver_ws = ScopeSolver(p, sparsity = range(10), sample_size = n, cv = 5,\n", + " split_method=lambda data, index: (data[0][index, :], data[1][index]))\n", + "solver_ws.solve(logistic_loss_cv, jit=True, data=(X, y))\n", "\n", "# Calculate runtime\n", "runtime = time.time() - start_time\n", @@ -486,7 +416,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 31, "id": "6343e161", "metadata": {}, "outputs": [ @@ -494,13 +424,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "True support set: (array([ 90, 97, 340, 395, 477]),)\n", + "True support set: [ 90 97 340 395 477]\n", "Estimated support set: [ 90 97 340 395 477]\n" ] } ], "source": [ - "print(\"True support set: \", (true_params.nonzero()))\n", + "print(\"True support set: \", (true_params.nonzero()[0]))\n", "print(\"Estimated support set: \", (solver_ws.support_set))" ] }, @@ -514,7 +444,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 32, "id": "90e52a60", "metadata": {}, "outputs": [ @@ -522,7 +452,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Runtime: 0.37964749336242676 seconds\n" + "Runtime: 6.12715482711792 seconds\n" ] } ], @@ -530,10 +460,11 @@ "# Record start time\n", "start_time = time.time()\n", "\n", - "solver_nws = ScopeSolver(p, s)\n", - "solver_nws.warm_start = False\n", - "params_nws = solver_nws.solve(logistic_loss, jit=True)\n", "\n", + "solver_nws = ScopeSolver(p, sparsity = range(10), sample_size = n, cv = 5,\n", + " split_method=lambda data, index: (data[0][index, :], data[1][index]))\n", + "solver_nws.warm_start = False\n", + "solver_nws.solve(logistic_loss_cv, jit=True, data=(X, y))\n", "# Calculate runtime\n", "runtime = time.time() - start_time\n", "print(\"Runtime:\", runtime, \"seconds\")" @@ -549,23 +480,15 @@ "name": "stdout", "output_type": "stream", "text": [ - "True support set: (array([ 90, 97, 340, 395, 477]),)\n", + "True support set: [ 90 97 340 395 477]\n", "Estimated support set: [ 90 97 340 395 477]\n" ] } ], "source": [ - "print(\"True support set: \", (true_params.nonzero()))\n", + "print(\"True support set: \", (true_params.nonzero()[0]))\n", "print(\"Estimated support set: \", (solver_nws.support_set))" ] - }, - { - "cell_type": "markdown", - "id": "f4e63bad", - "metadata": {}, - "source": [ - "Hint: all solvers default to using warmstart, which can slightly prolong computation time if not utilized" - ] } ], "metadata": { @@ -589,4 +512,4 @@ }, "nbformat": 4, "nbformat_minor": 5 -} \ No newline at end of file +} diff --git a/docs/source/gallery/LinearModelAndVariants/quantile-expectile-regression.ipynb b/docs/source/gallery/LinearModelAndVariants/quantile-expectile-regression.ipynb index 45cd709..76d5ad3 100644 --- a/docs/source/gallery/LinearModelAndVariants/quantile-expectile-regression.ipynb +++ b/docs/source/gallery/LinearModelAndVariants/quantile-expectile-regression.ipynb @@ -94,20 +94,12 @@ "execution_count": 2, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/zhujin/miniforge3/envs/convex-solver/lib/python3.9/site-packages/jax/_src/lib/__init__.py:33: UserWarning: JAX on Mac ARM machines is experimental and minimally tested. Please see https://github.com/google/jax/issues/5501 in the event of problems.\n", - " warnings.warn(\"JAX on Mac ARM machines is experimental and minimally tested. \"\n" - ] - }, { "name": "stdout", "output_type": "stream", "text": [ "Selected variables: [0 1 2 3], \n", - "estimated coefficients: [10.95208428 7.02401769 5.04306109 3.00177924]\n" + "estimated coefficients: [10.95206708 7.0240147 5.04308321 3.00179679]\n" ] } ], @@ -147,7 +139,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 3, @@ -156,7 +148,7 @@ }, { "data": { - "image/png": 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", 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", 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" ] @@ -195,9 +187,9 @@ "output_type": "stream", "text": [ "Selected variables: [0 1 2 3], \n", - "estimated coefficients: [8.97916353 6.99756945 4.99368271 2.98584495]\n", + "estimated coefficients: [8.97879982 6.9978618 4.99371648 2.98593456]\n", "Selected variables: [0 1 2 3], \n", - "estimated coefficients: [6.94788394 7.07152796 5.02274821 3.01699366]\n" + "estimated coefficients: [6.94784512 7.07070807 5.02209978 3.01848645]\n" ] } ], @@ -234,7 +226,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 5, @@ -243,7 +235,7 @@ }, { "data": { - "image/png": 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", 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", 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", 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", 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" ] @@ -369,11 +361,11 @@ "output_type": "stream", "text": [ "Selected variables: [0 1 2 3], \n", - "estimated coefficients: [10.40983627 7.01664256 5.02507904 3.0124289 ]\n", + "estimated coefficients: [10.40991352 7.01661672 5.02506633 3.01243308]\n", "Selected variables: [0 1 2 3], \n", - "estimated coefficients: [8.99668813 6.99586902 5.0008044 2.98165417]\n", + "estimated coefficients: [8.99668754 6.9958708 5.00080776 2.98165534]\n", "Selected variables: [0 1 2 3], \n", - "estimated coefficients: [7.54970328 7.02671685 5.03644048 2.95786884]\n" + "estimated coefficients: [7.5497228 7.02673697 5.03643977 2.95787651]\n" ] } ], @@ -417,7 +409,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 9, @@ -426,7 +418,7 @@ }, { "data": { - "image/png": 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", + "image/png": 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" ] @@ -511,7 +503,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.12" + "version": "3.10.13" }, "orig_nbformat": 4 }, diff --git a/docs/source/userguide/install.rst b/docs/source/userguide/install.rst index db22c4e..e1fc8a6 100644 --- a/docs/source/userguide/install.rst +++ b/docs/source/userguide/install.rst @@ -52,17 +52,6 @@ Note that ``--recurse-submodules`` is required since there are some submodules i Thanks to the editable mode with the flag ``-e``, we needn't re-build the package :ref:`skscope ` when the source python code changes. -If the dependence packages has been installed, we can build the package faster by - -.. code-block:: Bash - - python setup.py develop - -where the function of the flag ``develop`` is similar with ``-e`` of command ``pip``. - -This command will not check or prepare the required environment, so it can save a lot of time. -Thus, we can use ``pip`` with first building and ``python`` with re-building. - diff --git a/docs/source/userguide/quickstart.rst b/docs/source/userguide/quickstart.rst index 68eeb48..8997d4e 100644 --- a/docs/source/userguide/quickstart.rst +++ b/docs/source/userguide/quickstart.rst @@ -147,7 +147,7 @@ Further reading - `JAX library `__ -- A bunch of `machine learning methods `__ implemented on the ``skscope`` +- A bunch of `machine learning methods `__ implemented on the ``skscope`` - More `advanced features <../feature/index.html>`__ implemented in ``skscope`` diff --git a/docs/source/userguide/whatscope.rst b/docs/source/userguide/whatscope.rst index 3f00ab1..5131ef5 100644 --- a/docs/source/userguide/whatscope.rst +++ b/docs/source/userguide/whatscope.rst @@ -6,39 +6,39 @@ What is ``skscope``? ``skscope`` is a powerful open-source Python package specifically developed to tackle sparsity-constrained optimization (SCO) problems with utmost efficiency. With SCO's broad applicability in machine learning, statistics, signal processing, and other related domains, ``skscope`` can find extensive usage in these fields. For example, it excels in solving classic SCO problems like variable selection (also known as feature selection or compress sensing). Even more impressively, it goes beyond that and handles a diverse range of intriguing real-world problems: -1. `Robust variable selection `__ +1. `Robust variable selection `__ .. image:: figure/variable_selection.png :width: 300 :align: center -2. `Nonlinear variable selection `__ +2. `Nonlinear variable selection `__ .. image:: figure/nonlinear_variable_selection.png :width: 666 :align: center -3. `Spatial trend filtering `__ +3. `Spatial trend filtering `__ .. image:: figure/trend_filter.png :width: 666 :align: center -4. `Network reconstruction `__ +4. `Network reconstruction `__ .. image:: figure/precision_matrix.png :width: 666 :align: center -5. `Portfolio selection `__ +5. `Portfolio selection `__ .. image:: figure/portfolio_selection.png :width: 300 :align: center -These above examples represent just a glimpse of the practical problems that ``skscope`` can effectively address. With its efficient optimization algorithms and versatility, ``skscope`` proves to be an invaluable tool for a wide range of disciplines. Currently, we offer over 20 examples in our comprehensive `example gallery `__. +These above examples represent just a glimpse of the practical problems that ``skscope`` can effectively address. With its efficient optimization algorithms and versatility, ``skscope`` proves to be an invaluable tool for a wide range of disciplines. Currently, we offer over 20 examples in our comprehensive `example gallery `__. .. How does ``skscope`` work? diff --git a/skscope/utilities.py b/skscope/utilities.py index 5968469..229b300 100644 --- a/skscope/utilities.py +++ b/skscope/utilities.py @@ -31,11 +31,7 @@ def check_y_survival(y_or_event, *args, allow_all_censored=False): if len(args) == 0: y = y_or_event - if ( - not isinstance(y, np.ndarray) - or y.dtype.fields is None - or len(y.dtype.fields) != 2 - ): + if not isinstance(y, np.ndarray) or y.dtype.fields is None or len(y.dtype.fields) != 2: raise ValueError( "y must be a structured array with the first field" " being a binary class event indicator and the second field" @@ -51,9 +47,7 @@ def check_y_survival(y_or_event, *args, allow_all_censored=False): event = check_array(y_event, ensure_2d=False) if not np.issubdtype(event.dtype, np.bool_): - raise ValueError( - f"elements of event indicator must be boolean, but found {event.dtype}" - ) + raise ValueError(f"elements of event indicator must be boolean, but found {event.dtype}") if not (allow_all_censored or np.any(event)): raise ValueError("all samples are censored") @@ -66,9 +60,7 @@ def check_y_survival(y_or_event, *args, allow_all_censored=False): yt = check_array(yt, ensure_2d=False) if not np.issubdtype(yt.dtype, np.number): - raise ValueError( - f"time must be numeric, but found {yt.dtype} for argument {i + 2}" - ) + raise ValueError(f"time must be numeric, but found {yt.dtype} for argument {i + 2}") return_val.append(yt) @@ -106,7 +98,33 @@ def AIC( dimensionality: int, effective_params_num: int, train_size: int, -): +) -> float: + """ + Calculate the Akaike Information Criterion (AIC) for a given model. + + Parameters: + - objective_value (float): The value of the objective function (e.g., negative log-likelihood) for the model. + - dimensionality (int): The number of dimensions (features) in the model. + - effective_params_num (int): The number of effective parameters in the model. + - train_size (int): The size of the training dataset. + + Returns: + - float: The AIC value, which is a measure of the relative quality of the model for a given set of data. + Lower AIC values indicate a better model. + + Note: + When using information criteria (IC) functions, it is crucial to pay attention to different loss functions + for the same model. The correct IC implementation may vary. This function assumes the loss function is the + negative log-likelihood of the model. For example: + + def logistic_loss(params): + xbeta = X @ params + return jnp.sum(jnp.logaddexp(0, xbeta) - y * xbeta) + + If use `mean` rather than `sum` in `logistic_loss`, IC value may be wrong. + The AIC is calculated using the formula: + AIC = 2 * (objective_value + effective_params_num) + """ return 2 * objective_value + 2 * effective_params_num @@ -116,6 +134,32 @@ def BIC( effective_params_num: int, train_size: int, ): + """ + Calculate the Bayesian Information Criterion (BIC) for a given model. + + Parameters: + - objective_value (float): The value of the objective function (e.g., negative log-likelihood) for the model. + - dimensionality (int): The number of dimensions (features) in the model. + - effective_params_num (int): The number of effective parameters in the model. + - train_size (int): The size of the training dataset. + + Returns: + - float: The BIC value, which is a measure of the relative quality of the model for a given set of data. + Lower BIC values indicate a better model. + + Note: + When using information criteria (IC) functions, it is crucial to pay attention to different loss functions + for the same model. The correct IC implementation may vary. This function assumes the loss function is the + negative log-likelihood of the model. For example: + + def logistic_loss(params): + xbeta = X @ params + return jnp.sum(jnp.logaddexp(0, xbeta) - y * xbeta) + + If use `mean` rather than `sum` in `logistic_loss`, IC value may be wrong. + The BIC is calculated using the formula: + BIC = 2 * objective_value + effective_params_num * np.log(train_size) + """ return 2 * objective_value + effective_params_num * np.log(train_size) @@ -125,9 +169,33 @@ def SIC( effective_params_num: int, train_size: int, ): - return 2 * objective_value + effective_params_num * np.log( - np.log(train_size) - ) * np.log(dimensionality) + """ + Calculate the Special Information Criterion (SIC) for a given model. + + Parameters: + - objective_value (float): The value of the objective function (e.g., negative log-likelihood) for the model. + - dimensionality (int): The number of dimensions (features) in the model. + - effective_params_num (int): The number of effective parameters in the model. + - train_size (int): The size of the training dataset. + + Returns: + - float: The SIC value, which is a measure of the relative quality of the model for a given set of data. + Lower SIC values indicate a better model. + + Note: + When using information criteria (IC) functions, it is crucial to pay attention to different loss functions + for the same model. The correct IC implementation may vary. This function assumes the loss function is the + negative log-likelihood of the model. For example: + + def logistic_loss(params): + xbeta = X @ params + return jnp.sum(jnp.logaddexp(0, xbeta) - y * xbeta) + + If use `mean` rather than `sum` in `logistic_loss`, IC value may be wrong. + The SIC is calculated using the formula: + SIC = 2 * objective_value + effective_params_num * np.log(np.log(train_size)) * np.log(dimensionality) + """ + return 2 * objective_value + effective_params_num * np.log(np.log(train_size)) * np.log(dimensionality) def GIC( @@ -136,9 +204,34 @@ def GIC( effective_params_num: int, train_size: int, ): - return 2 * objective_value + effective_params_num * np.log( - np.log(train_size) - ) * np.log(dimensionality) + """ + Calculate the Generalized Information Criterion (GIC) for a given model, + GIC refers to specical information criterion (SIC) here. + + Parameters: + - objective_value (float): The value of the objective function (e.g., negative log-likelihood) for the model. + - dimensionality (int): The number of dimensions (features) in the model. + - effective_params_num (int): The number of effective parameters in the model. + - train_size (int): The size of the training dataset. + + Returns: + - float: The GIC value, which is a measure of the relative quality of the model for a given set of data. + Lower GIC values indicate a better model. + + Note: + When using information criteria (IC) functions, it is crucial to pay attention to different loss functions + for the same model. The correct IC implementation may vary. This function assumes the loss function is the + negative log-likelihood of the model. For example: + + def logistic_loss(params): + xbeta = X @ params + return jnp.sum(jnp.logaddexp(0, xbeta) - y * xbeta) + + If use `mean` rather than `sum` in `logistic_loss`, IC value may be wrong. + The GIC is calculated using the formula: + GIC = 2 * objective_value + effective_params_num * np.log(np.log(train_size)) * np.log(dimensionality) + """ + return 2 * objective_value + effective_params_num * np.log(np.log(train_size)) * np.log(dimensionality) def EBIC( @@ -147,9 +240,33 @@ def EBIC( effective_params_num: int, train_size: int, ): - return 2 * objective_value + effective_params_num * ( - np.log(train_size) + 2 * np.log(dimensionality) - ) + """ + Calculate the Extended Bayesian Information Criterion (EBIC) for a given model. + + Parameters: + - objective_value (float): The value of the objective function (e.g., negative log-likelihood) for the model. + - dimensionality (int): The number of dimensions (features) in the model. + - effective_params_num (int): The number of effective parameters in the model. + - train_size (int): The size of the training dataset. + + Returns: + - float: The EBIC value, which is a measure of the relative quality of the model for a given set of data. + Lower EBIC values indicate a better model. + + Note: + When using information criteria (IC) functions, it is crucial to pay attention to different loss functions + for the same model. The correct IC implementation may vary. This function assumes the loss function is the + negative log-likelihood of the model. For example: + + def logistic_loss(params): + xbeta = X @ params + return jnp.sum(jnp.logaddexp(0, xbeta) - y * xbeta) + + If use `mean` rather than `sum` in `logistic_loss`, IC value may be wrong. + The E is calculated using the formula: + EBIC = 2 * objective_value + effective_params_num * (np.log(train_size) + 2 * np.log(dimensionality)) + """ + return 2 * objective_value + effective_params_num * (np.log(train_size) + 2 * np.log(dimensionality)) def LinearSIC( @@ -158,9 +275,37 @@ def LinearSIC( effective_params_num: int, train_size: int, ): - return train_size * np.log(objective_value) + 2 * effective_params_num * np.log( - np.log(train_size) - ) * np.log(dimensionality) + """ + Calculate the Special Information Criterion (SIC) for a linear model. + + The difference between SIC and LinearSIC: + SIC assumes that the objective function is the negative logarithmic likelihood function of a statistical model; + LinearSIC assumes that the objective function is the sum of squared residuals, specifically adapted to linear models. + + Parameters: + - objective_value (float): The value of the objective function (e.g., negative log-likelihood) for the model. + - dimensionality (int): The number of dimensions (features) in the model. + - effective_params_num (int): The number of effective parameters in the model. + - train_size (int): The size of the training dataset. + + Returns: + - float: The LinearSIC value, which is a measure of the relative quality of the model for a given set of data. + Lower LinearSIC values indicate a better model. + + Note: + When using information criteria (IC) functions, it is crucial to pay attention to different loss functions + for the same model. The correct IC implementation may vary. This function assumes the loss function is the + negative log-likelihood of the model. For example: + + def linear_loss(params): + return jnp.sum(jnp.square(y - X @ params)) + + The LinearSIC is calculated using the formula: + LinearSIC = train_size * np.log(objective_value) + 2 * effective_params_num * np.log(np.log(train_size)) * np.log(dimensionality) + """ + return train_size * np.log(objective_value) + 2 * effective_params_num * np.log(np.log(train_size)) * np.log( + dimensionality + ) def LinearGIC( @@ -169,6 +314,35 @@ def LinearGIC( effective_params_num: int, train_size: int, ): - return train_size * np.log(objective_value) + 2 * effective_params_num * np.log( - np.log(train_size) - ) * np.log(dimensionality) + """ + Calculate the Generalized Information Criterion (GIC) for a linear model, + GIC refers to specical information criterion (SIC) here. + + The difference between GIC and LinearGIC: + GIC assumes that the objective function is the negative logarithmic likelihood function of a statistical model; + LinearGIC assumes that the objective function is the sum of squared residuals, specifically adapted to linear models. + + Parameters: + - objective_value (float): The value of the objective function (e.g., negative log-likelihood) for the model. + - dimensionality (int): The number of dimensions (features) in the model. + - effective_params_num (int): The number of effective parameters in the model. + - train_size (int): The size of the training dataset. + + Returns: + - float: The LinearGIC value, which is a measure of the relative quality of the model for a given set of data. + Lower LinearGIC values indicate a better model. + + Note: + When using information criteria (IC) functions, it is crucial to pay attention to different loss functions + for the same model. The correct IC implementation may vary. This function assumes the loss function is the + negative log-likelihood of the model. For example: + + def linear_loss(params): + return jnp.sum(jnp.square(y - X @ params)) + + The LinearGIC is calculated using the formula: + LinearGIC = train_size * np.log(objective_value) + 2 * effective_params_num * np.log(np.log(train_size)) * np.log(dimensionality) + """ + return train_size * np.log(objective_value) + 2 * effective_params_num * np.log(np.log(train_size)) * np.log( + dimensionality + )