diff --git a/doc/source/examples/FairSVM.ipynb b/doc/source/examples/FairSVM.ipynb index 5757aef..4fd9be6 100644 --- a/doc/source/examples/FairSVM.ipynb +++ b/doc/source/examples/FairSVM.ipynb @@ -8,7 +8,6 @@ "# **FairSVM**\n", "\n", "[![Slides](https://img.shields.io/badge/🦌-ReHLine-blueviolet)](https://rehline-python.readthedocs.io/en/latest/)\n", - "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1f_7t1t6FNxAooQOmpyhHCOVq0IKgMxe-?usp=sharing)\n", "\n", "The FairSVM solves the following optimization problem:\n", "\n", diff --git a/doc/source/examples/QR.ipynb b/doc/source/examples/QR.ipynb index 75640d9..f514554 100644 --- a/doc/source/examples/QR.ipynb +++ b/doc/source/examples/QR.ipynb @@ -8,7 +8,6 @@ "## **Ridge Quantile Regression**\n", "\n", "[![Slides](https://img.shields.io/badge/🦌-ReHLine-blueviolet)](https://rehline-python.readthedocs.io/en/latest/)\n", - "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1LwatjwjnMSB97eLVyuOiUY3sl3A3Ie__?usp=sharing)\n", "\n", "The regularized quantile regression solves the following optimization problem:\n", "\n", diff --git a/doc/source/examples/RankRegression.ipynb b/doc/source/examples/RankRegression.ipynb index 8858ad8..0bff4ac 100644 --- a/doc/source/examples/RankRegression.ipynb +++ b/doc/source/examples/RankRegression.ipynb @@ -1,28 +1,16 @@ { - "nbformat": 4, - "nbformat_minor": 0, - "metadata": { - "colab": { - "provenance": [] - }, - "kernelspec": { - "name": "python3", - "display_name": "Python 3" - }, - "language_info": { - "name": "python" - } - }, "cells": [ { "cell_type": "markdown", + "metadata": { + "id": "J0qXcTp-FofG" + }, "source": [ "\n", "# Rank Regression\n", "[![Slides](https://img.shields.io/badge/🦌-ReHLine-blueviolet)](https://rehline-python.readthedocs.io/en/latest/)\n", - "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/17X81EsmYRYMcdLjlxasGTs9uUuGqyuiy?usp=sharing)\n", "\n", - "Suppose we have a dataset $\\{(y_i,\\mathbf{x}_j)\\}_{i=1}^n$, where $y_i \\in \\mathbb{R}$ is the response and $\\mathbf{x_i} \\in \\mathbb{R}^{d}$ is the independent variable. Assume the data is generated from the following linear regression model,\n", + "Suppose we have a dataset $(y_i,\\mathbf{x}_j)_{i=1}^n$, where $y_i \\in \\mathbb{R}$ is the response and $\\mathbf{x}_i \\in \\mathbb{R}^{d}$ is the independent variable. Assume the data is generated from the following linear regression model,\n", "\n", "$$\n", " y_i = \\boldsymbol{\\beta}^{\\intercal}\\mathbf{x}_i + \\epsilon_i, \\quad i=1,2,\\cdots n,\n", @@ -36,12 +24,13 @@ "$$\n", "where $R_i^c(\\boldsymbol{\\beta})=R_i(\\boldsymbol{\\beta}) - \\frac{n+1}{2}$, $R_i(\\boldsymbol{\\beta})$ is the rank of ${y_i-\\boldsymbol{\\beta}^{\\intercal}\\mathbf{x}_i}$ among all $\\{ y_i-\\boldsymbol{\\beta}^{\\intercal}\\mathbf{x}_i\\}_{i=1}^n$. Canonically, we estimate $\\boldsymbol{\\beta}$ by solving the following optimization problem,\n", "\n", - "\n", "$$\n", " \\min_{\\boldsymbol{\\beta} \\in \\mathbb{R}^d} \\frac{2}{n(n-1)}\\sum\\limits_{1 \\leq i < j \\leq n} \\big| y_{ij} - \\boldsymbol{\\beta}^{\\intercal} \\mathbf{x}_{ij} \\big| \\tag{1}\n", "$$\n", - "where $\\mathbf{x}_{ij} = \\mathbf{x}_i - \\mathbf{x}_j$, $y_{ij}= y_i - y_j$. In the remaining part, I will show two methods to solve $(1)$ with implementations by rehline.\n", + "where $\\mathbf{x}_{ij} = \\mathbf{x}_i - \\mathbf{x}_j$, $y_{ij}= y_i - y_j$. In the remaining part, I will show two methods to solve $(1)$ with implementations via `rehline`.\n", "\n", + "In `ReHLine`, we have two options to solve rank regression: (i) use [Manual ReHLine Formulation](https://rehline-python.readthedocs.io/en/latest/tutorials/ReHLine_manual.html) based on `rehline.ReHLine`; (ii) use the form of [Empirical Risk Minimization](https://rehline-python.readthedocs.io/en/latest/tutorials/ReHLine_ERM.html) with the check loss based on `rehline.plqERM_Ridge`.\n", + "" + ] }, { "cell_type": "markdown", - "source": [ - "## Numerical example" - ], "metadata": { "id": "u3gEkxOBdUft" - } + }, + "source": [ + "## Numerical example" + ] }, { "cell_type": "markdown", + "metadata": { + "id": "CDuMki43tnuL" + }, "source": [ "### Preparation \n", "**Generate the data**" - ], - "metadata": { - "id": "CDuMki43tnuL" - } + ] }, { "cell_type": "code", @@ -102,49 +88,43 @@ }, { "cell_type": "markdown", - "source": [ - "**Differencing**" - ], "metadata": { "id": "8B62NsX7t2SS" - } + }, + "source": [ + "**Differencing**" + ] }, { "cell_type": "code", + "execution_count": 3, + "metadata": { + "id": "OcdNUtvrn_Hy" + }, + "outputs": [], "source": [ "# Differencing\n", "i, j = np.triu_indices(n, k=1)\n", "X_diff = (X[:, np.newaxis, :] - X[np.newaxis, :, :])[i,j]\n", "y_diff = (y[:, np.newaxis] - y[np.newaxis, :])[i,j]\n", "n_diff = y_diff.shape[0]" - ], - "metadata": { - "id": "OcdNUtvrn_Hy" - }, - "execution_count": 3, - "outputs": [] + ] }, { "cell_type": "markdown", + "metadata": { + "id": "VtuYCtgruBdK" + }, "source": [ - "### Solve the optimization problem by quantitle regression (QR)\n", + "### Method 1: Solve Rank Regression via `rehline.plqERM_Ridge`\n", "\n", "Since `rehline.plqERM_Ridge` support for check loss, we can directly use it to solve the problem.\n", "\n" - ], - "metadata": { - "id": "VtuYCtgruBdK" - } + ] }, { "cell_type": "code", - "source": [ - "# solve the problem use quantitle regression model with $\\tau = 0.5$ by reline\n", - "C = 4\n", - "quantile_regr = plqERM_Ridge(loss={'name': 'QR', 'qt': np.array([0.5])}, C=C, max_iter=10000)\n", - "quantile_regr.fit(X_diff, y_diff)\n", - "quantile_regr.coef_" - ], + "execution_count": 4, "metadata": { "colab": { "base_uri": "https://localhost:8080/" @@ -152,85 +132,87 @@ "id": "pNLvCXgO2KcT", "outputId": "7f205dd8-3daf-4cd6-ce8b-5e43c7a4ab57" }, - "execution_count": 4, "outputs": [ { - "output_type": "execute_result", "data": { "text/plain": [ "array([-0.68189333, -0.57733262, -2.21493922, -0.19351859])" ] }, + "execution_count": 4, "metadata": {}, - "execution_count": 4 + "output_type": "execute_result" } + ], + "source": [ + "# solve the problem use quantitle regression model with $\\tau = 0.5$ by reline\n", + "C = 4\n", + "quantile_regr = plqERM_Ridge(loss={'name': 'QR', 'qt': np.array([0.5])}, C=C, max_iter=10000)\n", + "quantile_regr.fit(X_diff, y_diff)\n", + "quantile_regr.coef_" ] }, { "cell_type": "markdown", + "metadata": { + "id": "_aE8U8k8t4Uq" + }, "source": [ - "### Solve the optimization problem by least absolute deviation model (LAD)\n", - "Since the LAD loss is a plq function, we can also use `rehline.RehLine` to solve it by manually specifying the ReLU-ReHU parameters.\n", + "### Method 2: Solve Rank Regression by `rehline.ReHLine`\n", + "Since the rank regression is a plq formulation, we can also use `rehline.RehLine` to solve it by manually specifying the ReLU-ReHU parameters.\n", "\n", "As shown in table 2 of (Dai and Qiu, 2024), when $L_i = C_i \\big| y_i - \\boldsymbol{\\beta}^{\\intercal} \\mathbf{x}_i \\big|$, ReLU parameters are as followed: $u_{1i}=C_i$, $v_{1i}=-C_i y_i$, $u_{2i}=-C_i$, $v_{2i}=C_i y_i$." - ], - "metadata": { - "id": "_aE8U8k8t4Uq" - } + ] }, { "cell_type": "code", - "source": [ - "# solve the problem use the least absolute deviation model (LAD)\n", - "C = 2\n", - "U = np.zeros(shape=(2,n_diff))\n", - "V = np.zeros(shape=(2,n_diff))\n", - "U[0,:], U[1,:] = C, -C\n", - "V[0,:], V[1,:] = -C * y_diff, C * y_diff\n", - "lad_regr = ReHLine(C=C, max_iter=10000)\n", - "lad_regr.U, lad_regr.V = U,V\n", - "lad_regr.fit(X_diff)\n", - "lad_regr.coef_" - ], + "execution_count": 5, "metadata": { - "id": "9BIbKUma39CH", "colab": { "base_uri": "https://localhost:8080/" }, + "id": "9BIbKUma39CH", "outputId": "1b663080-64df-4dc4-cee4-4acc5e4ef819" }, - "execution_count": 5, "outputs": [ { - "output_type": "execute_result", "data": { "text/plain": [ "array([-0.68189333, -0.57733262, -2.21493922, -0.19351859])" ] }, + "execution_count": 5, "metadata": {}, - "execution_count": 5 + "output_type": "execute_result" } + ], + "source": [ + "# solve the problem use the least absolute deviation model (LAD)\n", + "C = 2\n", + "U = np.zeros(shape=(2,n_diff))\n", + "V = np.zeros(shape=(2,n_diff))\n", + "U[0,:], U[1,:] = C, -C\n", + "V[0,:], V[1,:] = -C * y_diff, C * y_diff\n", + "lad_regr = ReHLine(C=C, max_iter=10000)\n", + "lad_regr.U, lad_regr.V = U,V\n", + "lad_regr.fit(X_diff)\n", + "lad_regr.coef_" ] }, { "cell_type": "markdown", + "metadata": { + "id": "pwPOUiEyeQfF" + }, "source": [ "### Results\n", "\n", "We compare the results of rank regression with OLS methods." - ], - "metadata": { - "id": "pwPOUiEyeQfF" - } + ] }, { "cell_type": "code", - "source": [ - "ols = LinearRegression(fit_intercept=False)\n", - "ols.fit(X, y)\n", - "ols.coef_" - ], + "execution_count": 6, "metadata": { "colab": { "base_uri": "https://localhost:8080/" @@ -238,27 +220,27 @@ "id": "Nvjfr8YbCsUM", "outputId": "46dd7432-4c08-4083-8672-fe3fae7e397d" }, - "execution_count": 6, "outputs": [ { - "output_type": "execute_result", "data": { "text/plain": [ "array([-0.66144318, -0.63704375, -2.25059478, -0.20229943])" ] }, + "execution_count": 6, "metadata": {}, - "execution_count": 6 + "output_type": "execute_result" } + ], + "source": [ + "ols = LinearRegression(fit_intercept=False)\n", + "ols.fit(X, y)\n", + "ols.coef_" ] }, { "cell_type": "code", - "source": [ - "from sklearn.metrics import r2_score\n", - "y_ols = ols.predict(X)\n", - "r2_score(y, y_ols)" - ], + "execution_count": 7, "metadata": { "colab": { "base_uri": "https://localhost:8080/" @@ -266,26 +248,27 @@ "id": "MLfypjNuHs7-", "outputId": "5c943d4b-e77b-421a-ab9e-e005d143c351" }, - "execution_count": 7, "outputs": [ { - "output_type": "execute_result", "data": { "text/plain": [ "0.681636901985671" ] }, + "execution_count": 7, "metadata": {}, - "execution_count": 7 + "output_type": "execute_result" } + ], + "source": [ + "from sklearn.metrics import r2_score\n", + "y_ols = ols.predict(X)\n", + "r2_score(y, y_ols)" ] }, { "cell_type": "code", - "source": [ - "y_rank = X.dot(quantile_regr.coef_)\n", - "r2_score(y, y_rank)" - ], + "execution_count": 8, "metadata": { "colab": { "base_uri": "https://localhost:8080/" @@ -293,34 +276,26 @@ "id": "z-e8Qcv6IAqT", "outputId": "8a023da7-4d99-4b55-cc80-3356141d6323" }, - "execution_count": 8, "outputs": [ { - "output_type": "execute_result", "data": { "text/plain": [ "0.680993625742062" ] }, + "execution_count": 8, "metadata": {}, - "execution_count": 8 + "output_type": "execute_result" } + ], + "source": [ + "y_rank = X.dot(quantile_regr.coef_)\n", + "r2_score(y, y_rank)" ] }, { "cell_type": "code", - "source": [ - "## plot QR results\n", - "import pandas as pd\n", - "import seaborn as sns\n", - "import matplotlib.pyplot as plt\n", - "\n", - "df = pd.DataFrame({'x0': X[:,0], 'y_true': y, 'ols': y_ols, 'rank': y_rank})\n", - "df = df.melt(id_vars='x0')\n", - "\n", - "sns.scatterplot(data=df, x='x0', y='value', hue='variable')\n", - "plt.show()" - ], + "execution_count": 9, "metadata": { "colab": { "base_uri": "https://localhost:8080/", @@ -329,30 +304,55 @@ "id": "MRfYZVttKIBW", "outputId": "0fb9128b-2c45-491e-e73e-55f75252373e" }, - "execution_count": 9, "outputs": [ { - "output_type": "display_data", "data": { + "image/png": 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", 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\n" + ] }, - "metadata": {} + "metadata": {}, + "output_type": "display_data" } + ], + "source": [ + "## plot QR results\n", + "import pandas as pd\n", + "import seaborn as sns\n", + "import matplotlib.pyplot as plt\n", + "\n", + "df = pd.DataFrame({'x0': X[:,0], 'y_true': y, 'ols': y_ols, 'rank': y_rank})\n", + "df = df.melt(id_vars='x0')\n", + "\n", + "sns.scatterplot(data=df, x='x0', y='value', hue='variable')\n", + "plt.show()" ] }, { "cell_type": "markdown", + "metadata": { + "id": "fivGfEGe8yhz" + }, "source": [ "## References\n", "[1] Jaeckel, L. A. (1972). Estimating regression coefficients by minimizing the dispersion of the residuals. _The Annals of Mathematical Statistics_, 1449-1458. \n", "[2] Dai, B., & Qiu, Y. (2024). ReHLine: regularized composite ReLU-ReHU loss minimization with linear computation and linear convergence. _Advances in Neural Information Processing Systems_, 36." - ], - "metadata": { - "id": "fivGfEGe8yhz" - } + ] + } + ], + "metadata": { + "colab": { + "provenance": [] + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + }, + "language_info": { + "name": "python" } - ] + }, + "nbformat": 4, + "nbformat_minor": 0 } diff --git a/doc/source/examples/SVM.ipynb b/doc/source/examples/SVM.ipynb index 7bbcc25..b52b29e 100644 --- a/doc/source/examples/SVM.ipynb +++ b/doc/source/examples/SVM.ipynb @@ -8,7 +8,6 @@ "# **SVM**\n", "\n", "[![Slides](https://img.shields.io/badge/🦌-ReHLine-blueviolet)](https://rehline-python.readthedocs.io/en/latest/)\n", - "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1f_7t1t6FNxAooQOmpyhHCOVq0IKgMxe-?usp=sharing)\n", "\n", "SVMs solve the following optimization problem:\n", "$$\n",