{"cells":[{"cell_type":"markdown","id":"e98f84a0","metadata":{"id":"e98f84a0"},"source":["[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](http://colab.research.google.com/github/ai2es/WAF_ML_Tutorial_Part1/blob/main/colab_notebooks/Notebook10_AHyperparameterSearch.ipynb)\n","\n","# Notebook 10: A hyperparameter search\n","\n","### Goal: Show an example of hyperparameter tuning \n","\n","#### Background\n","\n","If you look at any of the ML method documentation, you will find there are alot of switches and nobs you can play with. See this page on ```RandomForestRegressor``` [click](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestRegressor.html). Most of these switches and nobs are considered *hyperparameters*. In otherwords, these are parameters you can change that may or may not influence the machine learning model performance. Since every machine learning task is different, you often can *tune* your choice of these hyperparameters to get a better performing model. This notebook sets out to show you one way to do a hyperparameter search with random forest. \n","\n","#### Step 0: Get the github repo (we need some of the functions there)\n","\n","The first step with all of these Google Colab notebooks will be to grab the github repo and cd into the notebooks directory. \n","\n","To run things from the command line, put a ```!``` before your code\n","\n"," "]},{"cell_type":"code","source":["#get the github repo \n","!git clone https://github.com/ai2es/WAF_ML_Tutorial_Part1.git \n","\n","#cd into the repo so the paths work \n","import os \n","os.chdir('/content/WAF_ML_Tutorial_Part1/jupyter_notebooks/')"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"a2-riMK5fQe9","executionInfo":{"status":"ok","timestamp":1648654945664,"user_tz":300,"elapsed":26479,"user":{"displayName":"Randy C","userId":"12301342565919601334"}},"outputId":"000474ae-06fb-42ed-bbec-fbeddb56f3c2"},"id":"a2-riMK5fQe9","execution_count":1,"outputs":[{"output_type":"stream","name":"stdout","text":["Cloning into 'WAF_ML_Tutorial_Part1'...\n","remote: Enumerating objects: 301, done.\u001b[K\n","remote: Counting objects: 100% (301/301), done.\u001b[K\n","remote: Compressing objects: 100% (197/197), done.\u001b[K\n","remote: Total 301 (delta 139), reused 236 (delta 96), pack-reused 0\u001b[K\n","Receiving objects: 100% (301/301), 195.77 MiB | 14.92 MiB/s, done.\n","Resolving deltas: 100% (139/139), done.\n","Checking out files: 100% (100/100), done.\n"]}]},{"cell_type":"markdown","source":["# Import packages and load data for Regression\n","In the paper we do this hyperparameter tuning with the random forest regression example. So let's load in the regression dataset."],"metadata":{"id":"2FNgfluEfP6y"},"id":"2FNgfluEfP6y"},{"cell_type":"code","execution_count":2,"id":"ffdf6ca6-e815-4448-8cfc-3c48183ca635","metadata":{"id":"ffdf6ca6-e815-4448-8cfc-3c48183ca635","executionInfo":{"status":"ok","timestamp":1648654958463,"user_tz":300,"elapsed":7890,"user":{"displayName":"Randy C","userId":"12301342565919601334"}}},"outputs":[],"source":["###################################### Load training data ######################################\n","#import some helper functions for our other directory.\n","import sys\n","sys.path.insert(1, '../scripts/')\n","from aux_functions import load_n_combine_df\n","import numpy as np\n","(X_train,y_train),(X_validate,y_validate),_ = load_n_combine_df(path_to_data='../datasets/sevir/',features_to_keep=np.arange(0,36,1),class_labels=False,dropzeros=True)\n","\n","#remember since we have all 36 predictors we need to scale the inputs \n","from sklearn.preprocessing import StandardScaler\n","#create scaling object \n","scaler = StandardScaler()\n","#fit scaler to training data\n","scaler.fit(X_train)\n","#transform feature data into scaled space \n","X_train = scaler.transform(X_train)\n","X_validate = scaler.transform(X_validate)\n","################################################################################################\n","\n","#import other packages we will need \n","import pandas as pd \n","import matplotlib.pyplot as plt\n","\n","import matplotlib.patheffects as path_effects\n","pe1 = [path_effects.withStroke(linewidth=2,\n"," foreground=\"k\")]\n","pe2 = [path_effects.withStroke(linewidth=2,\n"," foreground=\"w\")]"]},{"cell_type":"markdown","id":"502f2a05-a55f-4105-b105-9789bb9bebf7","metadata":{"id":"502f2a05-a55f-4105-b105-9789bb9bebf7"},"source":["# Determine what parameter 'sweeps' you wish to do \n","\n","Right now I would like you to go check out the random forest document page: [here](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestRegressor.html). \n","\n","We will go ahead and systematically vary some of these hyperparameters. More specifically, we will play with\n","\n","1. Tree depth (i.e., number of branches).\n","2. Number of Trees \n","\n","While one could always do more hyperparameter tests, for now this will get you started on generally how to do it. Let's vary the depth of trees from 1 to 10, and we will incrementally increase it. Then for the number of trees lets do 1, 5, 10, 25, 50, 100. Note we did 1000 in the paper, but something you will notice is that the deeper the tree and the more numerous trees it takes longer to train your models. So for it not to take forever in this tutorial, we will cut it to 100. \n"]},{"cell_type":"code","execution_count":3,"id":"0af679aa-4122-48b9-b782-68d9742949a2","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"0af679aa-4122-48b9-b782-68d9742949a2","executionInfo":{"status":"ok","timestamp":1648654964391,"user_tz":300,"elapsed":203,"user":{"displayName":"Randy C","userId":"12301342565919601334"}},"outputId":"760b3e3e-35dd-4fc1-b906-9b4146fe7ac9"},"outputs":[{"output_type":"stream","name":"stdout","text":["[[1, 1], [1, 2], [1, 3], [1, 4], [1, 5], [1, 6], [1, 7], [1, 8], [1, 9], [1, 10], [5, 1], [5, 2], [5, 3], [5, 4], [5, 5], [5, 6], [5, 7], [5, 8], [5, 9], [5, 10], [10, 1], [10, 2], [10, 3], [10, 4], [10, 5], [10, 6], [10, 7], [10, 8], [10, 9], [10, 10], [25, 1], [25, 2], [25, 3], [25, 4], [25, 5], [25, 6], [25, 7], [25, 8], [25, 9], [25, 10], [50, 1], [50, 2], [50, 3], [50, 4], [50, 5], [50, 6], [50, 7], [50, 8], [50, 9], [50, 10], [100, 1], [100, 2], [100, 3], [100, 4], [100, 5], [100, 6], [100, 7], [100, 8], [100, 9], [100, 10]] 60\n"]}],"source":["#vary depth of trees from 1 to 10. \n","depth = np.arange(1,11,1)\n","#vary the number of trees in the forest from 1 to 100 \n","n_tree = [1,5,10,25,50,100]\n","\n","#build out the parameter sets we will test. \n","sets = []\n","#for each number of trees, set their depth\n","for n in n_tree:\n"," for d in depth:\n"," sets.append([n,d])\n"," \n","print(sets,len(sets))"]},{"cell_type":"markdown","id":"0a87faab-1f13-49fc-ab21-53275bb3882c","metadata":{"id":"0a87faab-1f13-49fc-ab21-53275bb3882c"},"source":["As you can see, we have built out 60 different parameters to try out! \n","\n","To make the code a bit more concise, let's define a functiont that will calculate all our metrics for us. "]},{"cell_type":"code","execution_count":4,"id":"c6a60be5-ce6d-4219-b725-8d2a7f65937d","metadata":{"id":"c6a60be5-ce6d-4219-b725-8d2a7f65937d","executionInfo":{"status":"ok","timestamp":1648654967348,"user_tz":300,"elapsed":187,"user":{"displayName":"Randy C","userId":"12301342565919601334"}}},"outputs":[],"source":["from gewitter_functions import get_bias,get_mae,get_rmse,get_r2\n","#define a function to calcualte all the metrics, and return a vector with all 4. \n","def get_metrics(model,X,y):\n"," yhat = model.predict(X)\n"," mae = get_mae(y,yhat)\n"," rmse = get_rmse(y,yhat)\n"," bias = get_bias(y,yhat)\n"," r2 = get_r2(y,yhat)\n"," return np.array([bias,mae,rmse,r2])"]},{"cell_type":"markdown","id":"9057a519-8ac4-4abe-b79c-aa6e1cabc2a7","metadata":{"id":"9057a519-8ac4-4abe-b79c-aa6e1cabc2a7"},"source":["Okay, now we are ready to do the hyperparameter sweep. \n","\n","WARNING, this took 60 mins on google colab with n_jobs set to 4. So if you dont have that kind of time, go ahead and jump past this cell, and just load the pre-computed metrics I have. "]},{"cell_type":"code","execution_count":5,"id":"49d1781e-7464-400d-94d4-b006fd4392f0","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"49d1781e-7464-400d-94d4-b006fd4392f0","executionInfo":{"status":"ok","timestamp":1648658326945,"user_tz":300,"elapsed":3357639,"user":{"displayName":"Randy C","userId":"12301342565919601334"}},"outputId":"d91c8bbf-0a3a-48e2-e70f-05aa613a2499"},"outputs":[{"output_type":"stream","name":"stderr","text":["100%|██████████| 60/60 [55:56<00:00, 55.95s/it] \n"]}],"source":["# import the progress bar so we can see how long this will take\n","import tqdm \n","\n","#import RandomForest \n","from sklearn.ensemble import RandomForestRegressor\n","\n","#do our hyperparameter search!\n","# for each set of parameters,train a new model and evaluate it \n","for i,s in enumerate(tqdm.tqdm(sets)):\n"," #initialize the model \n"," reg = RandomForestRegressor(n_estimators=s[0],max_depth=s[1],n_jobs=4)\n"," #train the model\n"," reg.fit(X_train,y_train)\n"," #get the metrics on both the training dataset and the validation dataset. \n"," met_train = get_metrics(reg,X_train,y_train)\n"," met_val = get_metrics(reg,X_validate,y_validate)\n"," \n"," #this if statement lets us stack the observations up. \n"," if i ==0:\n"," #if the first loop, rename things\n"," all_scores_val = met_val \n"," all_scores_train = met_train\n"," else:\n"," #otherwise, stack it on \n"," all_scores_val = np.vstack([all_scores_val,met_val])\n"," all_scores_train = np.vstack([all_scores_train,met_train])\n"," \n"," del reg \n","\n","#import pandas for easy writing and reading functions \n","import pandas as pd\n","\n","#this takes a hot min to run, so lets save them when we are done. \n","df_val = pd.DataFrame(all_scores_val,columns=['Bias','MeanAbsoluteError','RootMeanSquaredError','Rsquared'])\n","df_val.to_csv('../datasets/hyperparametersearch/validation_metrics.csv',index=False)\n","df_train = pd.DataFrame(all_scores_train,columns=['Bias','MeanAbsoluteError','RootMeanSquaredError','Rsquared'])\n","df_train.to_csv('../datasets/hyperparametersearch/train_metrics.csv',index=False)"]},{"cell_type":"markdown","id":"e807a37b-032e-4561-b3c8-0351bec0405c","metadata":{"id":"e807a37b-032e-4561-b3c8-0351bec0405c"},"source":["Since that took about 30 mins, we dont want to do that EVERY time we load this notebook, so lets save the results out to a file (i.e., a comma separated values file format) to allow for quick and easy reading later on. (this dataset is already made for you in the ```datasets``` folder in the repo.). "]},{"cell_type":"code","execution_count":6,"id":"1b736d69-c2b8-46ae-a5eb-e04d998d62d1","metadata":{"id":"1b736d69-c2b8-46ae-a5eb-e04d998d62d1","executionInfo":{"status":"ok","timestamp":1648658570036,"user_tz":300,"elapsed":164,"user":{"displayName":"Randy C","userId":"12301342565919601334"}}},"outputs":[],"source":["df_val = pd.read_csv('../datasets/hyperparametersearch/validation_metrics.csv').to_numpy()\n","df_train = pd.read_csv('../datasets/hyperparametersearch/train_metrics.csv').to_numpy()"]},{"cell_type":"markdown","id":"e7678c3f-a5d8-4b57-808d-aae467d053d1","metadata":{"id":"e7678c3f-a5d8-4b57-808d-aae467d053d1"},"source":["And there we go, we have successfully trained 60 models with various different configurations to see if any one particular configuration does better than another. So, how do we check which one is doing best? Well we can look at the validation dataset results, here I named it ```all_scores_val```. This will show us the general performance on the validation data. So lets take a look at that now. In the next cell is some code to plot up that matrix we saved out in the last cell. \n","\n","The figure I want to make has a metric on each panel. The x-axis will be the tree depth, then each color will be the number of trees. "]},{"cell_type":"code","execution_count":8,"id":"993cd862","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":386},"id":"993cd862","executionInfo":{"status":"ok","timestamp":1648658580939,"user_tz":300,"elapsed":3742,"user":{"displayName":"Randy C","userId":"12301342565919601334"}},"outputId":"b2af7b2a-ae7e-4aeb-99d1-930bf7abe01d"},"outputs":[{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:63: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n"]},{"output_type":"display_data","data":{"text/plain":["
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\n"},"metadata":{"image/png":{"width":422,"height":351}}}],"source":["#matplotlib things\n","import matplotlib.pyplot as plt \n","import matplotlib\n","from matplotlib.ticker import (MultipleLocator, FormatStrFormatter,\n"," AutoMinorLocator)\n","\n","#make default resolution of figures much higher (i.e., High definition)\n","%config InlineBackend.figure_format = 'retina'\n","\n","#plot parameters that I personally like, feel free to make these your own.\n","matplotlib.rcParams['axes.facecolor'] = [0.9,0.9,0.9] #makes a grey background to the axis face\n","matplotlib.rcParams['axes.labelsize'] = 14 #fontsize in pts\n","matplotlib.rcParams['axes.titlesize'] = 14 \n","matplotlib.rcParams['xtick.labelsize'] = 12 \n","matplotlib.rcParams['ytick.labelsize'] = 12 \n","matplotlib.rcParams['legend.fontsize'] = 12 \n","matplotlib.rcParams['legend.facecolor'] = 'w' \n","matplotlib.rcParams['savefig.transparent'] = False\n","\n","#make a 2 row, 2 column plot (4 total subplots)\n","fig,axes = plt.subplots(2,2,figsize=(5,5))\n","#set background color to white, otherwise its transparent when you copy paste it out of this notebook. \n","fig.set_facecolor('w')\n","\n","#lets ravel the 2x2 axes matrix to a 4x1 shape. This makes looping easier (in my opinion). \n","axes = axes.ravel()\n","\n","########### colormap stuff ###########\n","# I want to color each line by the number of trees. So this bit of code does that for us.\n","#get func to plot it\n","from aux_functions import make_colorbar\n","#grab colormap\n","cmap = matplotlib.cm.cividis\n","#set up the boundaries to each color \n","norm = matplotlib.colors.BoundaryNorm(n_tree, cmap.N)\n","#make a mappable so we can get the color based on the number of trees. \n","scalarMap = matplotlib.cm.ScalarMappable(norm=norm, cmap=cmap)\n","######################################\n","\n","titles = ['Bias','MAE','RMSE','$R^{2}$']\n","for j,ax in enumerate(axes):\n"," for i,ii in enumerate(n_tree):\n"," color_choice =scalarMap.to_rgba(ii)\n"," ax.plot(np.arange(1,11,1),df_val[(i*10):(i+1)*10,j],'o-',color=color_choice,ms=3)\n"," # ax.plot(np.arange(1,11,1),df_train[(i*10):(i+1)*10,j],'o--',color=color_choice,ms=3)\n"," ax.set_title(titles[j])\n"," ax.set_xlim([0,12])\n"," ax.grid('on')\n"," # ax.xaxis.grid(True, which='minor')\n"," # For the minor ticks, use no labels; default NullFormatter.\n"," ax.xaxis.set_minor_locator(MultipleLocator(1))\n"," ax.yaxis.set_minor_locator(MultipleLocator(2.5))\n"," \n","axes[2].set_xlabel('Tree Depth')\n","axes[3].set_xlabel('Tree Depth')\n","\n","########### draw and fill the colorbar ###########\n","ax_cbar = fig.add_axes([1.025, 0.4, 0.015,0.33])\n","cbar = make_colorbar(ax_cbar,1,100,cmap)\n","cbar.set_label('# of trees')\n","##################################################\n","\n","plt.tight_layout()"]},{"cell_type":"markdown","id":"9b30fa3a-cccf-473b-a237-bdc65ae8e591","metadata":{"id":"9b30fa3a-cccf-473b-a237-bdc65ae8e591"},"source":["A reminder that each x-axis as the tree depth (i.e., number of decisions; branches) and the y-axis is the metric that is indicated in the title. The color corresponds to the number of trees used in the random forest, with 1 being the darkest color and 100 being the lightest. \n","\n","As we can see, and noted in the paper, basically beyond using just 1 tree, which means its a decision tree, the number of trees doesnt have a large effect on the overall performance, while the number of trees seems to have a more appreciable effect. While this is helpful to find generally which models are performing better than others, there is a group of models that all seem to have similar performance with a tree depth greater than 5. \n","\n","In order to truly assess which one is best to use, we need to include the training data metrics. This is where we will diagnose when a model becomes *overfit*. Overfitting is when the training data performance is really good, but the validation performance is not good. To diagnose this, you compare on the plot when the training data continues to improve its performance while the validation performance starts to degrade or worsen. So lets add the training curves to the same plot as above."]},{"cell_type":"code","execution_count":10,"id":"a6c771a6-d5b9-4aac-9718-b986e58bc6e5","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":386},"id":"a6c771a6-d5b9-4aac-9718-b986e58bc6e5","executionInfo":{"status":"ok","timestamp":1648658592756,"user_tz":300,"elapsed":3021,"user":{"displayName":"Randy C","userId":"12301342565919601334"}},"outputId":"8720424f-606e-42c2-8386-6cec7e3678d9"},"outputs":[{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:45: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n"]},{"output_type":"display_data","data":{"text/plain":["
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\n"},"metadata":{"image/png":{"width":426,"height":351}}}],"source":["#make a 2 row, 2 column plot (4 total subplots)\n","fig,axes = plt.subplots(2,2,figsize=(5,5))\n","#set background color to white, otherwise its transparent when you copy paste it out of this notebook. \n","fig.set_facecolor('w')\n","\n","#lets ravel the 2x2 axes matrix to a 4x1 shape. This makes looping easier (in my opinion). \n","axes = axes.ravel()\n","\n","########### colormap stuff ###########\n","# I want to color each line by the number of trees. So this bit of code does that for us.\n","#get func to plot it\n","from aux_functions import make_colorbar\n","#grab colormap\n","cmap = matplotlib.cm.cividis\n","#set up the boundaries to each color \n","norm = matplotlib.colors.BoundaryNorm(n_tree, cmap.N)\n","#make a mappable so we can get the color based on the number of trees. \n","scalarMap = matplotlib.cm.ScalarMappable(norm=norm, cmap=cmap)\n","######################################\n","\n","titles = ['Bias','MAE','RMSE','$R^{2}$']\n","for j,ax in enumerate(axes):\n"," for i,ii in enumerate(n_tree):\n"," color_choice =scalarMap.to_rgba(ii)\n"," ax.plot(np.arange(1,11,1),df_val[(i*10):(i+1)*10,j],'o-',color=color_choice,ms=3)\n"," ax.plot(np.arange(1,11,1),df_train[(i*10):(i+1)*10,j],'^--',color=color_choice,ms=3)\n"," ax.axvline(8,ls='--',color='k')\n"," ax.set_title(titles[j])\n"," ax.set_xlim([0,12])\n"," ax.grid('on')\n"," # ax.xaxis.grid(True, which='minor')\n"," # For the minor ticks, use no labels; default NullFormatter.\n"," ax.xaxis.set_minor_locator(MultipleLocator(1))\n"," ax.yaxis.set_minor_locator(MultipleLocator(2.5))\n"," \n","axes[2].set_xlabel('Tree Depth')\n","axes[3].set_xlabel('Tree Depth')\n","\n","########### draw and fill the colorbar ###########\n","ax_cbar = fig.add_axes([1.025, 0.4, 0.015,0.33])\n","cbar = make_colorbar(ax_cbar,1,100,cmap)\n","cbar.set_label('# of trees')\n","##################################################\n","\n","plt.tight_layout()"]},{"cell_type":"markdown","id":"ddd5faa3-c318-43e3-9235-f0219caa62d9","metadata":{"id":"ddd5faa3-c318-43e3-9235-f0219caa62d9"},"source":["Okay, now we have the training curves in the dashed lines and triangle markers. I have also drawn a vertical dashed black line on the tree depth that seems to maximize performance before overfitting. We can see at a tree depth of 8, the $R^{2}$ value for the training data now out performs the validation data, while the other metrics are effectively the same as 5,6, and 7. Thats why we suggest random forest of > 1 tree and depth of 8 is likely a good model to continue on and use. \n","\n","I hope this was enough to give you an example of how to do hyperparameter tuning. I encourage you to go ahead and try it with the other models!"]}],"metadata":{"kernelspec":{"display_name":"waf_tutorial_part1","language":"python","name":"waf_tutorial_part1"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.10.2"},"colab":{"name":"Notebook10_AHyperparameterSearch.ipynb","provenance":[]}},"nbformat":4,"nbformat_minor":5}