diff --git a/README.md b/README.md index f8d1506..75a7712 100644 --- a/README.md +++ b/README.md @@ -25,15 +25,19 @@ ______________________________________________________________________ ## Introduction This is a set of tutorials for the CMS Machine Learning Hands-on Advanced Tutorial Session (HATS). -They are intended to show you how to build machine learning models in python, using `Keras`, `TensorFlow`, and `PyTorch`, and use them in your `ROOT`-based analyses. -We will build event-level classifiers for differentiating VBF Higgs and standard model background 4 muon events and jet-level classifiers for differentiating boosted W boson jets from QCD jets using dense and convolutional neural networks. +They are intended to show you how to build machine learning models in python, using `xgboost`, `Keras`, `TensorFlow`, and `PyTorch`, and use them in your `ROOT`-based analyses. + We will build event-level classifiers for differentiating VBF Higgs and standard model background 4 muon events and jet-level classifiers for differentiating boosted W boson jets from QCD jets using BDTs, and dense and convolutional neural networks. We will also explore more advanced models such as graph neural networks (GNNs), variational autoencoders (VAEs), and generative adversarial networks (GANs) on simple datasets. ## Setup -### Vanderbilt Jupyterhub (Recommended!) +### Purdue Analysis Facility (New and recommended!) -The recommended method for running the tutorials live is the Vanderbilt Jupyterhub, follow the instructions [here](https://fnallpc.github.io/machine-learning-hats/setup/vanderbilt-jupyterhub/vanderbilt.html). +The recommended method for running the tutorials live is the Purdue AF, follow the instructions [here](https://fnallpc.github.io/machine-learning-hats/setup/purdue/purdue.html). + +### Vanderbilt Jupyterhub + +Another option is the Vanderbilt Jupyterhub, instructions [here](https://fnallpc.github.io/machine-learning-hats/setup/vanderbilt-jupyterhub/vanderbilt.html). ### FNAL LPC diff --git a/machine-learning-hats/_toc.yml b/machine-learning-hats/_toc.yml index 9e7a380..b170b66 100644 --- a/machine-learning-hats/_toc.yml +++ b/machine-learning-hats/_toc.yml @@ -6,6 +6,7 @@ root: index parts: - caption: Setup chapters: + - file: setup/purdue/purdue - file: setup/vanderbilt-jupyterhub/vanderbilt - file: setup/lpc - file: setup-libraries @@ -14,12 +15,13 @@ parts: maxdepth: 2 chapters: - file: notebooks/1-datasets-uproot - - file: notebooks/2-dense + - file: notebooks/2-boosted-decision-tree + - file: notebooks/3-dense sections: - - file: notebooks/2.1-dense-keras - - file: notebooks/2.2-dense-pytorch - - file: notebooks/2.3-dense-bayesian-optimization - - file: notebooks/3-conv2d - - file: notebooks/4-gnn-cora - - file: notebooks/5-vae-mnist - - file: notebooks/6-gan-mnist \ No newline at end of file + - file: notebooks/3.1-dense-keras + - file: notebooks/3.2-dense-pytorch + - file: notebooks/3.3-dense-bayesian-optimization + - file: notebooks/4-conv2d + - file: notebooks/5-gnn-cora + - file: notebooks/6-vae-mnist + - file: notebooks/7-gan-mnist \ No newline at end of file diff --git a/machine-learning-hats/notebooks/1-datasets-uproot.ipynb b/machine-learning-hats/notebooks/1-datasets-uproot.ipynb index 896f64f..99514f1 100644 --- a/machine-learning-hats/notebooks/1-datasets-uproot.ipynb +++ b/machine-learning-hats/notebooks/1-datasets-uproot.ipynb @@ -23,7 +23,7 @@ }, { "cell_type": "code", - 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" 1550K .......... .......... .......... .......... .......... 36% 457K 2s\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - " 1600K .......... .......... .......... .......... .......... 37% 159M 1s\n", - " 1650K .......... .......... .......... .......... .......... 38% 170M 1s\n", - " 1700K .......... .......... .......... .......... .......... 39% 171M 1s\n", - " 1750K .......... .......... .......... .......... .......... 40% 453K 1s\n", - " 1800K .......... .......... .......... .......... .......... 42% 149M 1s\n", - " 1850K .......... .......... .......... .......... .......... 43% 158M 1s\n", - " 1900K .......... .......... .......... .......... .......... 44% 157M 1s\n", - " 1950K .......... .......... .......... .......... .......... 45% 136M 1s\n", - " 2000K .......... .......... .......... .......... .......... 46% 455K 1s\n", - " 2050K .......... .......... .......... .......... .......... 47% 93.7M 1s\n", - " 2100K .......... .......... .......... .......... .......... 48% 147M 1s\n", - " 2150K .......... .......... .......... .......... .......... 50% 138M 1s\n", - " 2200K .......... .......... .......... .......... .......... 51% 160M 1s\n", - " 2250K .......... .......... .......... .......... .......... 52% 146M 1s\n", - " 2300K .......... .......... .......... .......... .......... 53% 455K 1s\n", - " 2350K .......... .......... .......... .......... .......... 54% 119M 1s\n", - " 2400K .......... .......... .......... .......... .......... 55% 150M 1s\n", - " 2450K .......... .......... .......... .......... .......... 56% 150M 1s\n", - " 2500K .......... .......... .......... .......... .......... 57% 151M 1s\n", - " 2550K .......... .......... .......... .......... .......... 59% 136M 1s\n", - " 2600K .......... .......... .......... .......... .......... 60% 458K 1s\n", - " 2650K .......... .......... .......... .......... .......... 61% 97.6M 1s\n", - " 2700K .......... .......... .......... .......... .......... 62% 156M 1s\n", - " 2750K .......... .......... .......... .......... .......... 63% 131M 1s\n", - " 2800K .......... .......... .......... .......... .......... 64% 156M 1s\n", - " 2850K .......... .......... .......... .......... .......... 65% 110M 1s\n", - " 2900K .......... .......... .......... .......... .......... 67% 455K 1s\n", - " 2950K .......... .......... .......... .......... .......... 68% 136M 1s\n", - " 3000K .......... .......... .......... .......... .......... 69% 168M 1s\n", - " 3050K .......... .......... .......... .......... .......... 70% 164M 1s\n", - " 3100K .......... .......... .......... .......... .......... 71% 167M 1s\n", - " 3150K .......... .......... .......... .......... .......... 72% 460K 1s\n", - " 3200K .......... .......... .......... .......... .......... 73% 49.3M 1s\n", - " 3250K .......... .......... .......... .......... .......... 75% 155M 1s\n", - " 3300K .......... .......... .......... .......... .......... 76% 161M 0s\n", - " 3350K .......... .......... .......... .......... .......... 77% 148M 0s\n", - " 3400K .......... .......... .......... .......... .......... 78% 155M 0s\n", - " 3450K .......... .......... .......... .......... .......... 79% 461K 0s\n", - " 3500K .......... .......... .......... .......... .......... 80% 37.9M 0s\n", - " 3550K .......... .......... .......... .......... .......... 81% 122M 0s\n", - " 3600K .......... .......... .......... .......... .......... 82% 149M 0s\n", - " 3650K .......... .......... .......... .......... .......... 84% 157M 0s\n", - " 3700K .......... .......... .......... .......... .......... 85% 148M 0s\n", - " 3750K .......... .......... .......... .......... .......... 86% 457K 0s\n", - " 3800K .......... .......... .......... .......... .......... 87% 138M 0s\n", - " 3850K .......... .......... .......... .......... .......... 88% 133M 0s\n", - " 3900K .......... .......... .......... .......... .......... 89% 138M 0s\n", - " 3950K .......... .......... .......... .......... .......... 90% 121M 0s\n", - " 4000K .......... .......... .......... .......... .......... 92% 139M 0s\n", - " 4050K .......... .......... .......... .......... .......... 93% 456K 0s\n", - " 4100K .......... .......... .......... .......... .......... 94% 130M 0s\n", - " 4150K .......... .......... .......... .......... .......... 95% 132M 0s\n", - " 4200K .......... .......... .......... .......... .......... 96% 155M 0s\n", - " 4250K .......... .......... .......... .......... .......... 97% 139M 0s\n", - " 4300K .......... .......... .......... .......... .......... 98% 136M 0s\n", - " 4350K .......... .......... .......... .......... ......... 100% 457K=2.0s\n", - "\n", - "2023-08-12 00:12:44 (2.15 MB/s) - ‘data/ntuple_4mu_VV.root’ saved [4505518/4505518]\n", - "\n" - ] - } - ], + "outputs": [], "source": [ "%%bash\n", "mkdir -p data\n", @@ -383,86 +82,14 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "metadata": { "slideshow": { "slide_type": "" }, "tags": [] }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "name | typename | interpretation \n", - "---------------------+--------------------------+-------------------------------\n", - "f_run | int32_t | AsDtype('>i4')\n", - "f_lumi | int32_t | AsDtype('>i4')\n", - "f_event | int32_t | AsDtype('>i4')\n", - "f_weight | float | AsDtype('>f4')\n", - "f_int_weight | float | AsDtype('>f4')\n", - "f_pu_weight | float | AsDtype('>f4')\n", - "f_eff_weight | float | AsDtype('>f4')\n", - "f_lept1_pt | float | AsDtype('>f4')\n", - "f_lept1_eta | float | AsDtype('>f4')\n", - "f_lept1_phi | float | AsDtype('>f4')\n", - "f_lept1_charge | float | AsDtype('>f4')\n", - "f_lept1_pfx | float | AsDtype('>f4')\n", - "f_lept1_sip | float | AsDtype('>f4')\n", - "f_lept2_pt | float | AsDtype('>f4')\n", - "f_lept2_eta | float | AsDtype('>f4')\n", - "f_lept2_phi | float | AsDtype('>f4')\n", - "f_lept2_charge | float | AsDtype('>f4')\n", - "f_lept2_pfx | float | AsDtype('>f4')\n", - "f_lept2_sip | float | AsDtype('>f4')\n", - "f_lept3_pt | float | AsDtype('>f4')\n", - "f_lept3_eta | float | AsDtype('>f4')\n", - "f_lept3_phi | float | AsDtype('>f4')\n", - "f_lept3_charge | float | AsDtype('>f4')\n", - "f_lept3_pfx | float | AsDtype('>f4')\n", - "f_lept3_sip | float | AsDtype('>f4')\n", - "f_lept4_pt | float | AsDtype('>f4')\n", - "f_lept4_eta | float | AsDtype('>f4')\n", - "f_lept4_phi | float | AsDtype('>f4')\n", - "f_lept4_charge | float | AsDtype('>f4')\n", - "f_lept4_pfx | float | AsDtype('>f4')\n", - "f_lept4_sip | float | AsDtype('>f4')\n", - "f_iso_max | float | AsDtype('>f4')\n", - "f_sip_max | float | AsDtype('>f4')\n", - "f_Z1mass | float | AsDtype('>f4')\n", - "f_Z2mass | float | AsDtype('>f4')\n", - "f_angle_costhetastar | float | AsDtype('>f4')\n", - "f_angle_costheta1 | float | AsDtype('>f4')\n", - "f_angle_costheta2 | float | AsDtype('>f4')\n", - "f_angle_phi | float | AsDtype('>f4')\n", - "f_angle_phistar1 | float | AsDtype('>f4')\n", - "f_pt4l | float | AsDtype('>f4')\n", - "f_eta4l | float | AsDtype('>f4')\n", - "f_mass4l | float | AsDtype('>f4')\n", - "f_mass4lErr | float | AsDtype('>f4')\n", - "f_njets_pass | float | AsDtype('>f4')\n", - "f_deltajj | float | AsDtype('>f4')\n", - "f_massjj | float | AsDtype('>f4')\n", - "f_D_jet | float | AsDtype('>f4')\n", - "f_jet1_pt | float | AsDtype('>f4')\n", - "f_jet1_eta | float | AsDtype('>f4')\n", - "f_jet1_phi | float | AsDtype('>f4')\n", - "f_jet1_e | float | AsDtype('>f4')\n", - "f_jet2_pt | float | AsDtype('>f4')\n", - "f_jet2_eta | float | AsDtype('>f4')\n", - "f_jet2_phi | float | AsDtype('>f4')\n", - "f_jet2_e | float | AsDtype('>f4')\n", - "f_D_bkg_kin | float | AsDtype('>f4')\n", - "f_D_bkg | float | AsDtype('>f4')\n", - "f_D_gg | float | AsDtype('>f4')\n", - "f_D_g4 | float | AsDtype('>f4')\n", - "f_Djet_VAJHU | float | AsDtype('>f4')\n", - "f_pfmet | float | AsDtype('>f4')\n", - "None\n" - ] - } - ], + "outputs": [], "source": [ "import numpy as np\n", "import h5py\n", @@ -490,63 +117,19 @@ }, "source": [ "## Convert tree to `pandas` DataFrames\n", - "In my opinion, `pandas` DataFrames are a more convenient/flexible data container in python: https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.html. " + "`pandas` DataFrames can be a more convenient/flexible data container in python, especially for large amounts of data: https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.html. " ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": { "slideshow": { "slide_type": "" }, "tags": [] }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " f_mass4l f_massjj\n", - "0 91.098129 -999.0\n", - "(58107, 2)\n", - " f_mass4l f_massjj\n", - "0 91.098129 -999.0\n", - "[[ 91.09813 -999. ]\n", - " [ 201.84761 -999. ]\n", - " [ 89.279076 -999. ]\n", - " ...\n", - " [ 90.129845 -999. ]\n", - " [ 250.97742 -999. ]\n", - " [ 229.47015 -999. ]]\n", - "(58107, 2)\n", - "0 False\n", - "1 True\n", - "2 False\n", - "3 True\n", - "4 True\n", - " ... \n", - "58102 False\n", - "58103 True\n", - "58104 False\n", - "58105 True\n", - "58106 True\n", - "Name: f_mass4l, Length: 58107, dtype: bool\n", - "1 201.847610\n", - "3 586.597412\n", - "4 135.589798\n", - "5 734.903442\n", - "6 341.958466\n", - " ... \n", - "58097 225.355103\n", - "58098 214.074249\n", - "58103 252.845184\n", - "58105 250.977417\n", - "58106 229.470154\n", - "Name: f_mass4l, Length: 42219, dtype: float32\n" - ] - } - ], + "outputs": [], "source": [ "import pandas as pd\n", "\n", @@ -593,35 +176,14 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "metadata": { "slideshow": { "slide_type": "" }, "tags": [] }, - "outputs": [ - { - "data": { - "image/png": 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", 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "\n", @@ -630,21 +192,21 @@ "VARS = [\"f_mass4l\", \"f_massjj\"]\n", "\n", "plt.figure(figsize=(5, 4), dpi=100)\n", - "plt.xlabel(VARS[0])\n", "bins = np.linspace(80, 140, 100)\n", "df[\"bkg\"][VARS[0]].plot.hist(bins=bins, alpha=1, label=\"bkg\", histtype=\"step\")\n", "df[\"VV\"][VARS[0]].plot.hist(bins=bins, alpha=1, label=\"VV\", histtype=\"step\")\n", "plt.legend(loc=\"upper right\")\n", "plt.xlim(80, 140)\n", + "plt.xlabel(VARS[0])\n", + "plt.show()\n", "\n", "plt.figure(figsize=(5, 4), dpi=100)\n", - "plt.xlabel(VARS[1])\n", "bins = np.linspace(0, 2000, 100)\n", "df[\"bkg\"][VARS[1]].plot.hist(bins=bins, alpha=1, label=\"bkg\", histtype=\"step\")\n", "df[\"VV\"][VARS[1]].plot.hist(bins=bins, alpha=1, label=\"VV\", histtype=\"step\")\n", "plt.legend(loc=\"upper right\")\n", "plt.xlim(0, 2000)\n", - "\n", + "plt.xlabel(VARS[1])\n", "plt.show()" ] }, @@ -663,9 +225,9 @@ ], "metadata": { "kernelspec": { - "display_name": "machine-learning-hats", + "display_name": "machine-learning-hats-2023", "language": "python", - "name": "machine-learning-hats" + "name": "python3" }, "language_info": { "codemirror_mode": { diff --git a/machine-learning-hats/notebooks/2-boosted-decision-tree.ipynb b/machine-learning-hats/notebooks/2-boosted-decision-tree.ipynb new file mode 100644 index 0000000..c22e10b --- /dev/null +++ b/machine-learning-hats/notebooks/2-boosted-decision-tree.ipynb @@ -0,0 +1,556 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "" + }, + "tags": [] + }, + "source": [ + "# Boosted decision trees with xgboost\n", + "Authors: Raghav Kansal" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "" + }, + "tags": [] + }, + "source": [ + "Run this cell to download the data if you did not already download it in from Tutorial #1:" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "scrolled": true, + "slideshow": { + "slide_type": "" + }, + "tags": [ + "hide-output" + ] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--2024-01-09 17:58:50-- https://zenodo.org/record/3901869/files/ntuple_4mu_bkg.root?download=1\n", + "Resolving zenodo.org (zenodo.org)... 188.184.98.238, 188.184.103.159, 188.185.79.172, ...\n", + "Connecting to zenodo.org (zenodo.org)|188.184.98.238|:443... connected.\n", + "HTTP request sent, awaiting response... 301 MOVED PERMANENTLY\n", + "Location: /records/3901869/files/ntuple_4mu_bkg.root [following]\n", + "--2024-01-09 17:58:51-- https://zenodo.org/records/3901869/files/ntuple_4mu_bkg.root\n", + "Reusing existing connection to zenodo.org:443.\n", + "HTTP request sent, awaiting response... 200 OK\n", + "Length: 8867265 (8.5M) [application/octet-stream]\n", + "Saving to: ‘data/ntuple_4mu_bkg.root’\n", + "\n", + "100%[======================================>] 8,867,265 5.55MB/s in 1.5s \n", + "\n", + "2024-01-09 17:58:53 (5.55 MB/s) - ‘data/ntuple_4mu_bkg.root’ saved [8867265/8867265]\n", + "\n", + "--2024-01-09 17:58:53-- https://zenodo.org/record/3901869/files/ntuple_4mu_VV.root?download=1\n", + "Resolving zenodo.org (zenodo.org)... 188.184.98.238, 188.184.103.159, 188.185.79.172, ...\n", + "Connecting to zenodo.org (zenodo.org)|188.184.98.238|:443... connected.\n", + "HTTP request sent, awaiting response... 301 MOVED PERMANENTLY\n", + "Location: /records/3901869/files/ntuple_4mu_VV.root [following]\n", + "--2024-01-09 17:58:54-- https://zenodo.org/records/3901869/files/ntuple_4mu_VV.root\n", + "Reusing existing connection to zenodo.org:443.\n", + "HTTP request sent, awaiting response... 200 OK\n", + "Length: 4505518 (4.3M) [application/octet-stream]\n", + "Saving to: ‘data/ntuple_4mu_VV.root’\n", + "\n", + "100%[======================================>] 4,505,518 4.11MB/s in 1.0s \n", + "\n", + "2024-01-09 17:58:55 (4.11 MB/s) - ‘data/ntuple_4mu_VV.root’ saved [4505518/4505518]\n", + "\n" + ] + } + ], + "source": [ + "!mkdir -p data\n", + "!wget -O data/ntuple_4mu_bkg.root \"https://zenodo.org/record/3901869/files/ntuple_4mu_bkg.root?download=1\"\n", + "!wget -O data/ntuple_4mu_VV.root \"https://zenodo.org/record/3901869/files/ntuple_4mu_VV.root?download=1\"" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "" + }, + "tags": [] + }, + "source": [ + "## Loading `pandas` DataFrames\n", + "Now we load two different `NumPy` arrays. One corresponding to the VV signal and one corresponding to the background." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "slideshow": { + "slide_type": "" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "import uproot\n", + "import numpy as np\n", + "import pandas as pd\n", + "import h5py\n", + "\n", + "# fix random seed for reproducibility\n", + "seed = 7\n", + "np.random.seed(seed)\n", + "\n", + "treename = \"HZZ4LeptonsAnalysisReduced\"\n", + "filename = {}\n", + "upfile = {}\n", + "df = {}\n", + "\n", + "filename[\"VV\"] = \"data/ntuple_4mu_VV.root\"\n", + "filename[\"bkg\"] = \"data/ntuple_4mu_bkg.root\"\n", + "\n", + "VARS = [\"f_mass4l\", \"f_massjj\"] # choose which vars to use (2d)\n", + "\n", + "upfile[\"VV\"] = uproot.open(filename[\"VV\"])\n", + "upfile[\"bkg\"] = uproot.open(filename[\"bkg\"])\n", + "\n", + "df[\"bkg\"] = upfile[\"bkg\"][treename].arrays(VARS, library=\"pd\")\n", + "df[\"VV\"] = upfile[\"VV\"][treename].arrays(VARS, library=\"pd\")\n", + "\n", + "# cut out undefined variables VARS[0] and VARS[1] > -999\n", + "df[\"VV\"] = df[\"VV\"][(df[\"VV\"][VARS[0]] > -999) & (df[\"VV\"][VARS[1]] > -999)]\n", + "df[\"bkg\"] = df[\"bkg\"][(df[\"bkg\"][VARS[0]] > -999) & (df[\"bkg\"][VARS[1]] > -999)]\n", + "\n", + "# add isSignal variable\n", + "df[\"VV\"][\"isSignal\"] = np.ones(len(df[\"VV\"]))\n", + "df[\"bkg\"][\"isSignal\"] = np.zeros(len(df[\"bkg\"]))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "" + }, + "tags": [] + }, + "source": [ + "## Dividing the data into testing and training dataset\n", + "\n", + "We will split the data into two parts (one for training+validation and one for testing). " + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "slideshow": { + "slide_type": "" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "NDIM = len(VARS)\n", + "\n", + "df_all = pd.concat([df[\"VV\"], df[\"bkg\"]])\n", + "dataset = df_all.values\n", + "X = dataset[:, 0:NDIM]\n", + "Y = dataset[:, NDIM]\n", + "\n", + "from sklearn.model_selection import train_test_split\n", + "\n", + "X_train_val, X_test, Y_train_val, Y_test = train_test_split(X, Y, test_size=0.2, random_state=7)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "" + }, + "tags": [] + }, + "source": [ + "## Define the model\n", + "\n", + "We are using a simple boosted decision tree model from the xgboost library." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "slideshow": { + "slide_type": "" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "import xgboost as xgb\n", + "\n", + "# see https://xgboost.readthedocs.io/en/stable/python/python_api.html#xgboost.XGBClassifier\n", + "# for detailed explanations of parameters\n", + "model = xgb.XGBClassifier(\n", + " n_estimators=10, # number of boosting rounds (i.e. number of decision trees)\n", + " max_depth=1, # max depth of each decision tree\n", + " learning_rate=0.1,\n", + " early_stopping_rounds=5, # how many rounds to wait to see if the loss is going down\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "" + }, + "tags": [] + }, + "source": [ + "## Run training \n", + "Here, we run the training." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "scrolled": false, + "slideshow": { + "slide_type": "" + }, + "tags": [ + "output_scroll" + ] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[0]\tvalidation_0-logloss:0.48588\tvalidation_1-logloss:0.49037\n", + "[1]\tvalidation_0-logloss:0.43483\tvalidation_1-logloss:0.43617\n", + "[2]\tvalidation_0-logloss:0.39488\tvalidation_1-logloss:0.39379\n", + "[3]\tvalidation_0-logloss:0.36247\tvalidation_1-logloss:0.35934\n", + "[4]\tvalidation_0-logloss:0.33569\tvalidation_1-logloss:0.33082\n", + "[5]\tvalidation_0-logloss:0.31318\tvalidation_1-logloss:0.30684\n", + "[6]\tvalidation_0-logloss:0.29404\tvalidation_1-logloss:0.28647\n", + "[7]\tvalidation_0-logloss:0.27773\tvalidation_1-logloss:0.26900\n", + "[8]\tvalidation_0-logloss:0.26370\tvalidation_1-logloss:0.25397\n", + "[9]\tvalidation_0-logloss:0.24876\tvalidation_1-logloss:0.24161\n" + ] + } + ], + "source": [ + "trained_model = model.fit(\n", + " X_train_val,\n", + " Y_train_val,\n", + " # xgboost uses the last set for early stopping\n", + " # https://xgboost.readthedocs.io/en/stable/python/python_intro.html#early-stopping\n", + " eval_set=[(X_train_val, Y_train_val), (X_test, Y_test)], # sets for which to save the loss\n", + " verbose=True,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "" + }, + "tags": [] + }, + "source": [ + "## Plot performance\n", + "Here, we plot the history of the training and the performance in a ROC curve" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "slideshow": { + "slide_type": "" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "evals_result = trained_model.evals_result()\n", + "\n", + "fig = plt.figure(figsize=(5, 4))\n", + "for i, label in enumerate([\"Train\", \"Test\"]):\n", + " plt.plot(evals_result[f\"validation_{i}\"][\"logloss\"], label=label, linewidth=2)\n", + "\n", + "plt.xlabel(\"Epoch\")\n", + "plt.ylabel(\"Loss\")\n", + "plt.legend()\n", + "plt.show()\n", + "\n", + "\n", + "# Plot ROC\n", + "Y_predict = model.predict_proba(X_test)\n", + "from sklearn.metrics import roc_curve, auc\n", + "\n", + "fpr, tpr, thresholds = roc_curve(Y_test, Y_predict[:, 1])\n", + "roc_auc = auc(fpr, tpr)\n", + "\n", + "\n", + "fig, ax = plt.subplots(1, 1, figsize=(5, 4))\n", + "ax.plot(fpr, tpr, lw=2, color=\"cyan\", label=\"auc = %.3f\" % (roc_auc))\n", + "ax.plot([0, 1], [0, 1], linestyle=\"--\", lw=2, color=\"k\", label=\"random chance\")\n", + "ax.set_xlim([0, 1.0])\n", + "ax.set_ylim([0, 1.0])\n", + "ax.set_xlabel(\"false positive rate\")\n", + "ax.set_ylabel(\"true positive rate\")\n", + "ax.set_title(\"receiver operating curve\")\n", + "ax.legend(loc=\"lower right\")\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "slideshow": { + "slide_type": "" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " f_mass4l f_massjj isSignal bdt\n", + "0 125.077103 1300.426880 1.0 1\n", + "1 124.238113 437.221863 1.0 1\n", + "3 124.480667 1021.744080 1.0 1\n", + "4 124.919464 1101.381958 1.0 1\n", + "7 125.049065 498.717194 1.0 1\n" + ] + } + ], + "source": [ + "df_all[\"bdt\"] = model.predict(X) # add prediction to array\n", + "print(df_all.iloc[:5])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "" + }, + "tags": [] + }, + "source": [ + "## Plot BDT output vs input variables\n", + "Here, we will plot the BDT output and devision boundary as a function of the input variables." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "slideshow": { + "slide_type": "" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(200, 200)\n" + ] + } + ], + "source": [ + "# make a regular 2D grid for the inputs\n", + "myXI, myYI = np.meshgrid(np.linspace(0, 1500, 200), np.linspace(0, 6000, 200))\n", + "# print shape\n", + "print(myXI.shape)\n", + "\n", + "# run prediction at each point\n", + "myZI = model.predict_proba(np.c_[myXI.ravel(), myYI.ravel()])[:, 1]\n", + "myZI = myZI.reshape(myXI.shape)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "" + }, + "tags": [] + }, + "source": [ + "The code below shoes how to plot the BDT output and decision boundary. Does it look optimal?" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "slideshow": { + "slide_type": "" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from matplotlib.colors import ListedColormap\n", + "\n", + "plt.figure(figsize=(20, 7))\n", + "\n", + "# plot contour map of BDT output\n", + "# overlaid with test data points\n", + "ax = plt.subplot(1, 2, 1)\n", + "cm = plt.cm.RdBu\n", + "cm_bright = ListedColormap([\"#FF0000\", \"#0000FF\"])\n", + "cont_plot = ax.contourf(myXI, myYI, myZI, cmap=cm, alpha=0.8)\n", + "ax.scatter(X_test[:, 0], X_test[:, 1], c=Y_test, cmap=cm_bright, edgecolors=\"k\")\n", + "ax.set_xlabel(VARS[0])\n", + "ax.set_ylabel(VARS[1])\n", + "plt.colorbar(cont_plot, ax=ax, boundaries=[0, 1], label=\"NN output\")\n", + "\n", + "# plot decision boundary\n", + "# overlaid with test data points\n", + "ax = plt.subplot(1, 2, 2)\n", + "cm = plt.cm.RdBu\n", + "cm_bright = ListedColormap([\"#FF0000\", \"#0000FF\"])\n", + "cont_plot = ax.contourf(myXI, myYI, myZI > 0.5, cmap=cm, alpha=0.8)\n", + "ax.scatter(X_test[:, 0], X_test[:, 1], c=Y_test, cmap=cm_bright, edgecolors=\"k\")\n", + "ax.set_xlabel(VARS[0])\n", + "ax.set_ylabel(VARS[1])\n", + "plt.colorbar(cont_plot, ax=ax, boundaries=[0, 1], label=\"NN output\")\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Feature Importances\n", + "\n", + "A nice feature of xgboost is that you can plot the relative importance of each feature to the BDT decision. Does this plot make sense?" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "xgb.plot_importance(trained_model, grid=False)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "" + }, + "tags": [] + }, + "source": [ + "**Question 1:** Can you explain the loss curve?\n", + "\n", + "**Question 2:** Can you explain the decision boundary?\n", + "\n", + "**Question 3:** How can you improve the BDT preformance?\n", + "\n", + "**Question 4:** What happens if you add/remove early stopping?" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "machine-learning-das", + "language": "python", + "name": "machine-learning-das" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.0" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/machine-learning-hats/notebooks/2-dense.md b/machine-learning-hats/notebooks/3-dense.md similarity index 100% rename from machine-learning-hats/notebooks/2-dense.md rename to machine-learning-hats/notebooks/3-dense.md diff --git a/machine-learning-hats/notebooks/2.1-dense-keras.ipynb b/machine-learning-hats/notebooks/3.1-dense-keras.ipynb similarity index 100% rename from machine-learning-hats/notebooks/2.1-dense-keras.ipynb rename to machine-learning-hats/notebooks/3.1-dense-keras.ipynb diff --git a/machine-learning-hats/notebooks/2.2-dense-pytorch.ipynb b/machine-learning-hats/notebooks/3.2-dense-pytorch.ipynb similarity index 100% rename from machine-learning-hats/notebooks/2.2-dense-pytorch.ipynb rename to machine-learning-hats/notebooks/3.2-dense-pytorch.ipynb diff --git a/machine-learning-hats/notebooks/2.3-dense-bayesian-optimization.ipynb b/machine-learning-hats/notebooks/3.3-dense-bayesian-optimization.ipynb similarity index 100% rename from machine-learning-hats/notebooks/2.3-dense-bayesian-optimization.ipynb rename to machine-learning-hats/notebooks/3.3-dense-bayesian-optimization.ipynb diff --git a/machine-learning-hats/notebooks/3-conv2d.ipynb b/machine-learning-hats/notebooks/4-conv2d.ipynb similarity index 99% rename from machine-learning-hats/notebooks/3-conv2d.ipynb rename to machine-learning-hats/notebooks/4-conv2d.ipynb index 551c399..dcc2745 100644 --- a/machine-learning-hats/notebooks/3-conv2d.ipynb +++ b/machine-learning-hats/notebooks/4-conv2d.ipynb @@ -55,14 +55,13 @@ "### Convolution Operation\n", "Two-dimensional convolutional layer for image height $H$, width $W$, number of input channels $C$, number of output kernels (filters) $N$, and kernel height $J$ and width $K$ is given by:\n", "\n", - "\\begin{align}\n", - "\\label{convLayer}\n", - "\\boldsymbol{Y}[v,u,n] &= \\boldsymbol{\\beta}[n] + \\sum_{c=1}^{C} \\sum_{j=1}^{J} \\sum_{k=1}^{K} \\boldsymbol{X}[v+j,u+k,c]\\, \\boldsymbol{W}[j,k,c,n]\\,,\n", - "\\end{align}\n", + "$$\n", + "\\boldsymbol{Y}[v,u,n] = \\boldsymbol{\\beta}[n] + \\sum_{c=1}^{C} \\sum_{j=1}^{J} \\sum_{k=1}^{K} \\boldsymbol{X}[v+j,u+k,c]\\, \\boldsymbol{W}[j,k,c,n]\\,,\n", + "$$\n", "\n", "where $Y$ is the output tensor of size $V \\times U \\times N$, $W$ is the weight tensor of size $J \\times K \\times C \\times N$ and $\\beta$ is the bias vector of length $N$ .\n", "\n", - "The example below has $C=1$ input channel and $N=1$ ($J\\times K=3\\times 3$) kernel [credit](https://towardsdatascience.com/types-of-convolution-kernels-simplified-f040cb307c37):\n", + "The example below has $C=1$ input channel and $N=1$ ($J\\times K=3\\times 3$) kernel ([credit](https://towardsdatascience.com/types-of-convolution-kernels-simplified-f040cb307c37)):\n", "\n", "![convolution](https://miro.medium.com/v2/resize:fit:780/1*Eai425FYQQSNOaahTXqtgg.gif)" ] @@ -84,7 +83,7 @@ "source": [ "### Pooling\n", "\n", - "We also add pooling layers to reduce the image size between layers. For example, max pooling: (also from [here]([page](https://cs231n.github.io/convolutional-networks/))\n", + "We also add pooling layers to reduce the image size between layers. For example, max pooling (also from [here]([page](https://cs231n.github.io/convolutional-networks/))):\n", "\n", "![maxpool](https://cs231n.github.io/assets/cnn/maxpool.jpeg)" ] diff --git a/machine-learning-hats/notebooks/4-gnn-cora.ipynb b/machine-learning-hats/notebooks/5-gnn-cora.ipynb similarity index 99% rename from machine-learning-hats/notebooks/4-gnn-cora.ipynb rename to machine-learning-hats/notebooks/5-gnn-cora.ipynb index 180f253..acd6fe1 100644 --- a/machine-learning-hats/notebooks/4-gnn-cora.ipynb +++ b/machine-learning-hats/notebooks/5-gnn-cora.ipynb @@ -7,6 +7,8 @@ "source": [ "# Graph Neural Network (GNN) with PyTorch Geometric\n", "\n", + "Authors: Savannah Thais, Tony Aportela\n", + "\n", "The contents of this tutorial are heavily adapted from a similar one make by [Savannah Thais](https://github.com/savvy379) using tensorflow and keras.\n", "\n", "A graph $G=(N,E)$, comprising of nodes $N$ and edges $E$, is a versatile mathematical structure that can represent various data such as molecules, social networks, transportation systems, etc. Nodes and edges may have associated features like geometric or non-geometric information. Graphs can be directed or undirected, and GNNs, with their ability to handle graphs of varying shapes and sizes, are well-suited for diverse applications including High Energy Physics (HEP). \n", @@ -493,7 +495,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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", 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" ] diff --git a/machine-learning-hats/notebooks/5-vae-mnist.ipynb b/machine-learning-hats/notebooks/6-vae-mnist.ipynb similarity index 100% rename from machine-learning-hats/notebooks/5-vae-mnist.ipynb rename to machine-learning-hats/notebooks/6-vae-mnist.ipynb diff --git a/machine-learning-hats/notebooks/6-gan-mnist.ipynb b/machine-learning-hats/notebooks/7-gan-mnist.ipynb similarity index 100% rename from machine-learning-hats/notebooks/6-gan-mnist.ipynb rename to machine-learning-hats/notebooks/7-gan-mnist.ipynb diff --git a/machine-learning-hats/setup/purdue/folders.png b/machine-learning-hats/setup/purdue/folders.png new file mode 100644 index 0000000..3760222 Binary files /dev/null and b/machine-learning-hats/setup/purdue/folders.png differ diff --git a/machine-learning-hats/setup/purdue/git.png b/machine-learning-hats/setup/purdue/git.png new file mode 100644 index 0000000..1e97976 Binary files /dev/null and b/machine-learning-hats/setup/purdue/git.png differ diff --git a/machine-learning-hats/setup/purdue/purdue.md b/machine-learning-hats/setup/purdue/purdue.md new file mode 100644 index 0000000..e180761 --- /dev/null +++ b/machine-learning-hats/setup/purdue/purdue.md @@ -0,0 +1,33 @@ +# Purdue Analysis Facility + +## 1. Sign-in + +See the [Getting Started](https://analysis-facility.physics.purdue.edu/en/latest/doc-getting-started.html) guide and the rest of the documentation for details. + +Point your browser to https://cms.geddes.rcac.purdue.edu/hub and log in with your CERN or FNAL account. + +Create an instance with the default resources. + + +## 2. Clone this repository + +1. Once the session starts, open the Git sidebar menu: + +![git menu](git.png) + +2. Click "Clone a Repository". + +3. Copy and paste the repository URL: https://github.com/FNALLPC/machine-learning-hats.git and Clone with the default options. + +4. You should now see the `machine-learning-hats` directory in your file browser: + +![folders](folders.png) + +Open it and navigate to `machine-learning-hats` -> `notebooks` + + +## 3. Notebooks + +Open up a notebook and use the `Python3 kernel (default)` kernel. You can now the run the notebook by pressing `Shift + Enter`, one cell at a time. + + diff --git a/requirements.txt b/requirements.txt index c85ebef..407473d 100644 --- a/requirements.txt +++ b/requirements.txt @@ -10,4 +10,5 @@ pandas torch ipykernel tqdm -jupyter \ No newline at end of file +jupyter +xgboost \ No newline at end of file