From 0504e8a143ecc001afc586ecbacd8ab683a9b355 Mon Sep 17 00:00:00 2001 From: Giorgio Morales Luna Date: Thu, 21 Mar 2024 20:10:10 -0600 Subject: [PATCH] Updated README.md --- DualAQD_PredictionIntervals.ipynb | 692 +++++++++++++++--------------- README.md | 60 +++ 2 files changed, 406 insertions(+), 346 deletions(-) diff --git a/DualAQD_PredictionIntervals.ipynb b/DualAQD_PredictionIntervals.ipynb index 0d6df10..d2427c5 100644 --- a/DualAQD_PredictionIntervals.ipynb +++ b/DualAQD_PredictionIntervals.ipynb @@ -1,381 +1,381 @@ { - "nbformat": 4, - "nbformat_minor": 0, - "metadata": { + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "provenance": [] + }, + "kernelspec": { + "name": "python3", + "display_name": "Python 3" + }, + "language_info": { + "name": "python" + } + }, + "cells": [ + { + "cell_type": "markdown", + "source": [ + "# DualAQD: Dual Accuracy-quality-driven Prediction Intervals\n", + "\n", + "This Google Colab implements the PI-generation method explained in the paper \"[Dual Accuracy-Quality-Driven Neural Network for Prediction Interval Generation](https://arxiv.org/pdf/2212.06370.pdf).\"\n", + "\n", + "## Installation\n", + "\n", + "Execute `!pip install git+https://github.com/NISL-MSU/PredictionIntervals` in the terminal." + ], + "metadata": { + "id": "QnpZn0iHrUHY" + } + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { "colab": { - "provenance": [] + "base_uri": "https://localhost:8080/" }, - "kernelspec": { - "name": "python3", - "display_name": "Python 3" - }, - "language_info": { - "name": "python" + "id": "37nRoWU5o7Sq", + "outputId": "921d355e-e78d-4bda-cac7-df339c48c573" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + " Installing build dependencies ... \u001B[?25l\u001B[?25hdone\n", + " Getting requirements to build wheel ... \u001B[?25l\u001B[?25hdone\n", + " Installing backend dependencies ... \u001B[?25l\u001B[?25hdone\n", + " Preparing metadata (pyproject.toml) ... \u001B[?25l\u001B[?25hdone\n", + " Preparing metadata (setup.py) ... \u001B[?25l\u001B[?25hdone\n", + "\u001B[2K \u001B[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[32m334.7/334.7 kB\u001B[0m \u001B[31m6.2 MB/s\u001B[0m eta \u001B[36m0:00:00\u001B[0m\n", + "\u001B[2K \u001B[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[32m79.5/79.5 kB\u001B[0m \u001B[31m6.1 MB/s\u001B[0m eta \u001B[36m0:00:00\u001B[0m\n", + "\u001B[2K \u001B[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001B[0m \u001B[32m117.0/117.0 kB\u001B[0m \u001B[31m10.5 MB/s\u001B[0m eta \u001B[36m0:00:00\u001B[0m\n", + "\u001B[?25h Preparing metadata (setup.py) ... \u001B[?25l\u001B[?25hdone\n", + " Building wheel for PredictionIntervals (pyproject.toml) ... \u001B[?25l\u001B[?25hdone\n", + " Building wheel for antlr4-python3-runtime (setup.py) ... \u001B[?25l\u001B[?25hdone\n", + " Building wheel for timeout-decorator (setup.py) ... \u001B[?25l\u001B[?25hdone\n" + ] } + ], + "source": [ + "!pip install -q git+https://github.com/NISL-MSU/PredictionIntervals" + ] }, - "cells": [ + { + "cell_type": "markdown", + "source": [ + "## Load your data\n", + "\n", + "Given a regression problem, you only need to provide two matrices: `X` (explainable variables) and `Y` (response variable) as numPy arrays.\n", + "\n", + "In this example, we'll load a synthetic dataset:" + ], + "metadata": { + "id": "9fkpfl2Sryy6" + } + }, + { + "cell_type": "code", + "source": [ + "import numpy as np\n", + "from PredictionIntervals.utils import create_synth_data\n", + "X, Y, P1, P2 = create_synth_data(n=1500, plot=True)\n", + "\n", + "# Let's separate 1/3 of the data for training, 1/3 for validation, and 1/3 for test (modify these values to fit your needs)\n", + "indices = np.arange(len(Y))\n", + "np.random.seed(7)\n", + "np.random.shuffle(indices)\n", + "Xtrain, Ytrain = X[indices[:int(len(Y)/3)]], Y[indices[:int(len(Y)/3)]]\n", + "Xval, Yval = X[indices[int(len(Y)/3):int(len(Y)/3*2)]], Y[indices[int(len(Y)/3):int(len(Y)/3*2)]]\n", + "Xtest, Ytest = X[indices[int(len(Y)/3*2):]], Y[indices[int(len(Y)/3*2):]]" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 291 + }, + "id": "NP826vD_rTL5", + "outputId": "abfb9afe-265b-422d-ca03-f594ddbc8535" + }, + "execution_count": null, + "outputs": [ { - "cell_type": "markdown", - "source": [ - "# DualAQD: Dual Accuracy-quality-driven Prediction Intervals\n", - "\n", - "This Google Colab implements the PI-generation method explained in the paper \"[Dual Accuracy-Quality-Driven Neural Network for Prediction Interval Generation](https://arxiv.org/pdf/2212.06370.pdf).\"\n", - "\n", - "## Installation\n", - "\n", - "Execute `!pip install git+https://github.com/NISL-MSU/PredictionIntervals` in the terminal." + "output_type": "display_data", + "data": { + "text/plain": [ + "
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\n" + }, + "metadata": {} + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "## Train the models\n", + "\n", + "DualAQD uses two neural networks: a target-estimation network $f$ that is trained to generate accurate estimates, and a PI-generation NN $g$ that produces the upper and lower bounds of a prediction interval.\n", + "\n", + "We'll start by creating an instance of the class `PredictionIntervalsTrainer.`\n", + "\n", + "**Parameters**:\n", + "\n", + "* `X`: Input data (explainable variables). 2-D numpy array, shape (#samples, #features)\n", + "* `Y`: Target data (response variable). 1-D numpy array, shape (#samples, #features)\n", + "* `Xval`: Validation input data. 2-D numpy array, shape (#samples, #features)\n", + "* `Yval`: Validation target data. 1-D numpy array, shape (#samples, #features)\n", + "* `method`: PI-generation method. Options: 'DualAQD' or '[MCDropout](https://arxiv.org/pdf/1709.01907.pdf)'\n", + "* `normData`: If True, apply z-score normalization to the inputs and min-max normalization to the outputs\n", + "\n", + "**Note**: Normalization is applied to the training set; then, the exact same scaling is applied to the validation set." + ], + "metadata": { + "id": "BzSkKO0Xvmg2" + } + }, + { + "cell_type": "code", + "source": [ + "from PredictionIntervals.Trainer.TrainNN import Trainer\n", + "trainer = Trainer(X=Xtrain, Y=Ytrain, Xval=Xval, Yval=Yval)" + ], + "metadata": { + "id": "fSOGtMe-yysi" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "markdown", + "source": [ + "\n", + "To train the model, we'll call the `train` method.\n", + "\n", + "**Parameters**:\n", + "\n", + "* `batch_size`: Mini batch size. It is recommended a small number. *default: 16*\n", + "* `epochs`: Number of training epochs *default: 1000*\n", + "* `eta_`: Scale factor used to update the self-adaptive coefficient lambda (Eq. 6 of the paper). *default: 0.01*\n", + "* `printProcess`: If True, print the training process (loss and validation metrics after each epoch). *default: False*\n", + "* `plotCurves`: If True, plot the training and validation curves at the end of the training process\n", + "\n", + "**IMPORTANT**: This code is implemented using Pytorch. If you're running this on Google Colab, change the runtime type to GPU to accelerate the training process!" + ], + "metadata": { + "id": "ttE4CZKgy14p" + } + }, + { + "cell_type": "code", + "source": [ + "trainer.train(printProcess=False, epochs=2000, batch_size=16, plotCurves=True)" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 753 }, + "id": "RQQ-aQJdzW1u", + "outputId": "d2bb9877-65cf-4cc8-8caa-028107ee3b3d" + }, + "execution_count": null, + "outputs": [ { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "37nRoWU5o7Sq", - "outputId": "921d355e-e78d-4bda-cac7-df339c48c573" - }, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": [ - " Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n", - " Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n", - " Installing backend dependencies ... \u001b[?25l\u001b[?25hdone\n", - " Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n", - " Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n", - "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m334.7/334.7 kB\u001b[0m \u001b[31m6.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", - "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m79.5/79.5 kB\u001b[0m \u001b[31m6.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", - "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m117.0/117.0 kB\u001b[0m \u001b[31m10.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", - "\u001b[?25h Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n", - " Building wheel for PredictionIntervals (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n", - " Building wheel for antlr4-python3-runtime (setup.py) ... \u001b[?25l\u001b[?25hdone\n", - " Building wheel for timeout-decorator (setup.py) ... \u001b[?25l\u001b[?25hdone\n" - ] - } - ], - "source": [ - "!pip install -q git+https://github.com/NISL-MSU/PredictionIntervals" - ] + "output_type": "stream", + "name": "stdout", + "text": [ + "Training base model...\n" + ] }, { - "cell_type": "markdown", - "source": [ - "## Load your data\n", - "\n", - "Given a regression problem, you only need to provide two matrices: `X` (explainable variables) and `Y` (response variable) as numPy arrays.\n", - "\n", - "In this example, we'll load a synthetic dataset:" - ], - "metadata": { - "id": "9fkpfl2Sryy6" - } + "output_type": "stream", + "name": "stderr", + "text": [ + " 71%|███████▏ | 1429/2000 [04:07<01:39, 5.77it/s]\n" + ] }, { - "cell_type": "code", - "source": [ - "import numpy as np\n", - "from PredictionIntervals.utils import create_synth_data\n", - "X, Y, P1, P2 = create_synth_data(n=1500, plot=True)\n", - "\n", - "# Let's separate 1/3 of the data for training, 1/3 for validation, and 1/3 for test (modify these values to fit your needs)\n", - "indices = np.arange(len(Y))\n", - "np.random.seed(7)\n", - "np.random.shuffle(indices)\n", - "Xtrain, Ytrain = X[indices[:int(len(Y)/3)]], Y[indices[:int(len(Y)/3)]]\n", - "Xval, Yval = X[indices[int(len(Y)/3):int(len(Y)/3*2)]], Y[indices[int(len(Y)/3):int(len(Y)/3*2)]]\n", - "Xtest, Ytest = X[indices[int(len(Y)/3*2):]], Y[indices[int(len(Y)/3*2):]]" - ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 291 - }, - "id": "NP826vD_rTL5", - "outputId": "abfb9afe-265b-422d-ca03-f594ddbc8535" - }, - "execution_count": null, - "outputs": [ - { - "output_type": "display_data", - "data": { - "text/plain": [ - "
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\n" - }, - "metadata": {} - } - ] + "output_type": "stream", + "name": "stdout", + "text": [ + "Early stopping at epoch: 1429\n", + "Base model training complete!\n" + ] }, { - "cell_type": "markdown", - "source": [ - "## Train the models\n", - "\n", - "DualAQD uses two neural networks: a target-estimation network $f$ that is trained to generate accurate estimates, and a PI-generation NN $g$ that produces the upper and lower bounds of a prediction interval.\n", - "\n", - "We'll start by creating an instance of the class `PredictionIntervalsTrainer.`\n", - "\n", - "**Parameters**:\n", - "\n", - "* `X`: Input data (explainable variables). 2-D numpy array, shape (#samples, #features)\n", - "* `Y`: Target data (response variable). 1-D numpy array, shape (#samples, #features)\n", - "* `Xval`: Validation input data. 2-D numpy array, shape (#samples, #features)\n", - "* `Yval`: Validation target data. 1-D numpy array, shape (#samples, #features)\n", - "* `method`: PI-generation method. Options: 'DualAQD' or '[MCDropout](https://arxiv.org/pdf/1709.01907.pdf)'\n", - "* `normData`: If True, apply z-score normalization to the inputs and min-max normalization to the outputs\n", - "\n", - "**Note**: Normalization is applied to the training set; then, the exact same scaling is applied to the validation set." - ], - "metadata": { - "id": "BzSkKO0Xvmg2" - } + "output_type": "stream", + "name": "stderr", + "text": [ + " 60%|██████ | 1200/2000 [07:24<04:56, 2.70it/s]" + ] }, { - "cell_type": "code", - "source": [ - "from PredictionIntervals.Trainer.TrainNN import Trainer\n", - "trainer = Trainer(X=Xtrain, Y=Ytrain, Xval=Xval, Yval=Yval)" - ], - "metadata": { - "id": "fSOGtMe-yysi" - }, - "execution_count": null, - "outputs": [] + "output_type": "stream", + "name": "stdout", + "text": [ + "Early stopping at epoch: 1200\n" + ] }, { - "cell_type": "markdown", - "source": [ - "\n", - "To train the model, we'll call the `train` method, whose **parameters**\n", - "\n", - "**Parameters**:\n", - "\n", - "* `batch_size`: Mini batch size. It is recommended a small number. *default: 16*\n", - "* `epochs`: Number of training epochs *default: 1000*\n", - "* `eta_`: Scale factor used to update the self-adaptive coefficient lambda (Eq. 6 of the paper). *default: 0.01*\n", - "* `printProcess`: If True, print the training process (loss and validation metrics after each epoch). *default: False*\n", - "* `plotCurves`: If True, plot the training and validation curves at the end of the training process\n", - "\n", - "**IMPORTANT**: This code is implemented using Pytorch. If you're running this on Google Colab, change the runtime type to GPU to accelerate the training process!" - ], - "metadata": { - "id": "ttE4CZKgy14p" - } + "output_type": "stream", + "name": "stderr", + "text": [ + "\n" + ] }, { - "cell_type": "code", - "source": [ - "trainer.train(printProcess=False, epochs=2000, batch_size=16, plotCurves=True)" - ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 753 - }, - "id": "RQQ-aQJdzW1u", - "outputId": "d2bb9877-65cf-4cc8-8caa-028107ee3b3d" - }, - "execution_count": null, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": [ - "Training base model...\n" - ] - }, - { - "output_type": "stream", - "name": "stderr", - "text": [ - " 71%|███████▏ | 1429/2000 [04:07<01:39, 5.77it/s]\n" - ] - }, - { - "output_type": "stream", - "name": "stdout", - "text": [ - "Early stopping at epoch: 1429\n", - "Base model training complete!\n" - ] - }, - { - "output_type": "stream", - "name": "stderr", - "text": [ - " 60%|██████ | 1200/2000 [07:24<04:56, 2.70it/s]" - ] - }, - { - "output_type": "stream", - "name": "stdout", - "text": [ - "Early stopping at epoch: 1200\n" - ] - }, - { - "output_type": "stream", - "name": "stderr", - "text": [ - "\n" - ] - }, - { - "output_type": "stream", - "name": "stdout", - "text": [ - "\n", - "Validation performance:\n", - "Val MSE: 5.726753111596238 Val PICP: 0.949999988079071 Val MPIW: 7.315248966217041\n" - ] - }, - { - "output_type": "display_data", - "data": { - "text/plain": [ - "
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\n" 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\n" - }, - "metadata": {} - } - ] + "output_type": "stream", + "name": "stdout", + "text": [ + "\n", + "Validation performance:\n", + "Val MSE: 5.726753111596238 Val PICP: 0.949999988079071 Val MPIW: 7.315248966217041\n" + ] }, { - "cell_type": "markdown", - "source": [ - "It is worth mentioning that the loss function of DualAQD is $Loss_{DualAQD} = \\mathcal{L}_1 + \\lambda \\, \\mathcal{L}_2$; that is, it involves the minimization of two objectives. $\\mathcal{L}_1$ is related to a penalization of the PI width (Eq. 3 of the paper), $\\mathcal{L}_2$ enforces the PI integrity (Eq. 4), and $\\lambda$ is a self-adaptive coefficient that controls the relative importance of $\\mathcal{L}_1$ and $\\mathcal{L}_2$.\n", - "\n", - "From the second figure obtained by the previous cell, we notice the evolution of the $λ$ coefficient as it it tries the balance the trade-off between both objectives." + "output_type": "display_data", + "data": { + "text/plain": [ + "
" ], - "metadata": { - "id": "ze5NHb1NjHhY" - } + "image/png": 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\n" + }, + "metadata": {} }, { - "cell_type": "markdown", - "source": [ - "## Evaluate the model on the test set\n", - "\n", - "To do this, we call the method `evaluate`.\n", - "\n", - "**Parameters**:\n", - "\n", - "* `Xeval`: Evaluation data\n", - "* `Yeval`: Optional. Evaluation targets. *default: None*\n", - "* `normData`: If True, apply the same normalization that was applied to the training set\n", - "\n", - "**Note**: `Yeval` is *None* in the case that the target values of the evaluation data are not known.\n", - "\n", - "**Returns**:\n", - "* If `Yeval` is *None*: It returns predictions `ypred, y_u, y_l` (i.e., target predictions, PI upper bounds, and PI lower bounds).\n", - "* If `Yeval` is not *None*: It returns performance metrics and predictions `mse, PICP, MPIW, ypred, y_u, y_l` (i.e., mean square error of target predictions, PI coverage probability, mean PI width, target predictions, PI upper bounds, and PI lower bounds).\n", - "\n", - "\n" + "output_type": "display_data", + "data": { + "text/plain": [ + "
" ], - "metadata": { - "id": "sgxKUTL7FlrV" - } + "image/png": 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\n" + }, + "metadata": {} + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "It is worth mentioning that the loss function of DualAQD is $Loss_{DualAQD} = \\mathcal{L}_1 + \\lambda \\, \\mathcal{L}_2$; that is, it involves the minimization of two objectives. $\\mathcal{L}_1$ is related to a penalization of the PI width (Eq. 3 of the paper), $\\mathcal{L}_2$ enforces the PI integrity (Eq. 4), and $\\lambda$ is a self-adaptive coefficient that controls the relative importance of $\\mathcal{L}_1$ and $\\mathcal{L}_2$.\n", + "\n", + "From the second figure obtained by the previous cell, we notice the evolution of the $λ$ coefficient as it it tries the balance the trade-off between both objectives." + ], + "metadata": { + "id": "ze5NHb1NjHhY" + } + }, + { + "cell_type": "markdown", + "source": [ + "## Evaluate the model on the test set\n", + "\n", + "To do this, we call the method `evaluate`.\n", + "\n", + "**Parameters**:\n", + "\n", + "* `Xeval`: Evaluation data\n", + "* `Yeval`: Optional. Evaluation targets. *default: None*\n", + "* `normData`: If True, apply the same normalization that was applied to the training set\n", + "\n", + "**Note**: `Yeval` is *None* in the case that the target values of the evaluation data are not known.\n", + "\n", + "**Returns**:\n", + "* If `Yeval` is *None*: It returns predictions `ypred, y_u, y_l` (i.e., target predictions, PI upper bounds, and PI lower bounds).\n", + "* If `Yeval` is not *None*: It returns performance metrics and predictions `mse, PICP, MPIW, ypred, y_u, y_l` (i.e., mean square error of target predictions, PI coverage probability, mean PI width, target predictions, PI upper bounds, and PI lower bounds).\n", + "\n", + "\n" + ], + "metadata": { + "id": "sgxKUTL7FlrV" + } + }, + { + "cell_type": "code", + "source": [ + "val_mse, PICP, MPIW, ypred, y_u, y_l = trainer.evaluate(Xtest, Ytest, normData=True)\n", + "print('Test Performance:')\n", + "print(\"Test MSE: \" + str(val_mse) + \" Test PICP: \" + str(PICP) + \" Test MPIW: \" + str(MPIW))" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" }, + "id": "c9463TtmFkRF", + "outputId": "fb31a771-dd1d-488d-a506-b4ba9b19c11b" + }, + "execution_count": null, + "outputs": [ { - "cell_type": "code", - "source": [ - "val_mse, PICP, MPIW, ypred, y_u, y_l = trainer.evaluate(Xtest, Ytest, normData=True)\n", - "print('Test Performance:')\n", - "print(\"Test MSE: \" + str(val_mse) + \" Test PICP: \" + str(PICP) + \" Test MPIW: \" + str(MPIW))" - ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "c9463TtmFkRF", - "outputId": "fb31a771-dd1d-488d-a506-b4ba9b19c11b" - }, - "execution_count": null, - "outputs": [ - { - "output_type": "stream", - "name": "stdout", - "text": [ - "Test Performance:\n", - "Test MSE: 5.201604879034826 Test PICP: 0.9559999704360962 Test MPIW: 7.2122907638549805\n" - ] - } - ] + "output_type": "stream", + "name": "stdout", + "text": [ + "Test Performance:\n", + "Test MSE: 5.201604879034826 Test PICP: 0.9559999704360962 Test MPIW: 7.2122907638549805\n" + ] + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "## Plot Results" + ], + "metadata": { + "id": "YihU3A5mKcum" + } + }, + { + "cell_type": "code", + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "plt.figure()\n", + "plt.scatter(Xtest, Ytest, label='Observed Test Data', s=24)\n", + "plt.scatter(Xtest, ypred, label='Predicted Data', s=24)\n", + "plt.scatter(Xtest, y_u, label='Predicted Upper Bounds', s=24)\n", + "plt.scatter(Xtest, y_l, label='Predicted Lower Bounds', s=24, c='gold')\n", + "plt.fill_between(X, P1, P2, color='gray', alpha=0.5, linewidth=0, label='Ideal 95% PIs')\n", + "plt.legend(loc=\"lower right\")\n", + "plt.title('DualAQD')\n", + "plt.xlabel('x')\n", + "plt.ylabel('y')" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 489 }, + "id": "drGEpqSVKhsP", + "outputId": "e9191243-9534-4722-975c-b4e19d784f95" + }, + "execution_count": null, + "outputs": [ { - "cell_type": "markdown", - "source": [ - "## Plot Results" - ], - "metadata": { - "id": "YihU3A5mKcum" - } + "output_type": "execute_result", + "data": { + "text/plain": [ + "Text(0, 0.5, 'y')" + ] + }, + "metadata": {}, + "execution_count": 6 }, { - "cell_type": "code", - "source": [ - "import matplotlib.pyplot as plt\n", - "\n", - "plt.figure()\n", - "plt.scatter(Xtest, Ytest, label='Observed Test Data', s=24)\n", - "plt.scatter(Xtest, ypred, label='Predicted Data', s=24)\n", - "plt.scatter(Xtest, y_u, label='Predicted Upper Bounds', s=24)\n", - "plt.scatter(Xtest, y_l, label='Predicted Lower Bounds', s=24, c='gold')\n", - "plt.fill_between(X, P1, P2, color='gray', alpha=0.5, linewidth=0, label='Ideal 95% PIs')\n", - "plt.legend(loc=\"lower right\")\n", - "plt.title('DualAQD')\n", - "plt.xlabel('x')\n", - "plt.ylabel('y')" + "output_type": "display_data", + "data": { + "text/plain": [ + "
" ], - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 489 - }, - "id": "drGEpqSVKhsP", - "outputId": "e9191243-9534-4722-975c-b4e19d784f95" - }, - "execution_count": null, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": [ - "Text(0, 0.5, 'y')" - ] - }, - "metadata": {}, - "execution_count": 6 - }, - { - "output_type": "display_data", - "data": { - "text/plain": [ - "
" - ], - "image/png": 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\n" 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\n" + }, + "metadata": {} } - ] -} \ No newline at end of file + ] + } + ] +} diff --git a/README.md b/README.md index 3a12b37..6dc8d0d 100644 --- a/README.md +++ b/README.md @@ -28,6 +28,40 @@ You can also try the package on [Google Colab](https://colab.research.google.com ## Usage +### Train the models + +DualAQD uses two neural networks: a target-estimation network $f$ that is trained to generate accurate estimates, and a PI-generation NN $g$ that produces the upper and lower bounds of a prediction interval. + +First, create an instance of the class `PredictionIntervalsTrainer.` + +**Parameters**: + +* `X`: Input data (explainable variables). 2-D numpy array, shape (#samples, #features) +* `Y`: Target data (response variable). 1-D numpy array, shape (#samples, #features) +* `Xval`: Validation input data. 2-D numpy array, shape (#samples, #features) +* `Yval`: Validation target data. 1-D numpy array, shape (#samples, #features) +* `method`: PI-generation method. Options: 'DualAQD' or '[MCDropout](https://arxiv.org/pdf/1709.01907.pdf)' +* `normData`: If True, apply z-score normalization to the inputs and min-max normalization to the outputs + +**Note**: Normalization is applied to the training set; then, the exact same scaling is applied to the validation set. + +```python +from PredictionIntervals.Trainer.TrainNN import Trainer +trainer = Trainer(X=Xtrain, Y=Ytrain, Xval=Xval, Yval=Yval) +``` + +To train the model, we'll call the `train` method. + +**Parameters**: + +* `batch_size`: Mini batch size. It is recommended a small number. *default: 16* +* `epochs`: Number of training epochs *default: 1000* +* `eta_`: Scale factor used to update the self-adaptive coefficient lambda (Eq. 6 of the paper). *default: 0.01* +* `printProcess`: If True, print the training process (loss and validation metrics after each epoch). *default: False* +* `plotCurves`: If True, plot the training and validation curves at the end of the training process + +## Repository Structure + This repository contains the following scripts: * `PIGenerator.py`: Contains the PIGenerator class that is used to perform cross-validation using different NN-based PI-generation methods. @@ -36,6 +70,32 @@ This repository contains the following scripts: * `models/network.py`: Defines the network architecture. * `Demo.ipynb`: Jupyter notebook demo using a synthetic dataset. +```python +trainer.train(printProcess=False, epochs=2000, batch_size=16, plotCurves=True) +``` + +### Evaluate the model on the test set + +To do this, we call the method `evaluate`. + +**Parameters**: + +* `Xeval`: Evaluation data +* `Yeval`: Optional. Evaluation targets. *default: None* +* `normData`: If True, apply the same normalization that was applied to the training set + +**Note**: `Yeval` is *None* in the case that the target values of the evaluation data are not known. + +**Returns**: +* If `Yeval` is *None*: It returns predictions `ypred, y_u, y_l` (i.e., target predictions, PI upper bounds, and PI lower bounds). +* If `Yeval` is not *None*: It returns performance metrics and predictions `mse, PICP, MPIW, ypred, y_u, y_l` (i.e., mean square error of target predictions, PI coverage probability, mean PI width, target predictions, PI upper bounds, and PI lower bounds). + +```python +val_mse, PICP, MPIW, ypred, y_u, y_l = trainer.evaluate(Xtest, Ytest, normData=True) +print('Test Performance:') +print("Test MSE: " + str(val_mse) + " Test PICP: " + str(PICP) + " Test MPIW: " + str(MPIW)) +``` + # Citation Use this Bibtex to cite this repository