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@twolodzko
Last active April 12, 2020 17:19
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Hyperparameter tuning using `hyperopt` package
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Hyperparameter tuning using `hyperopt` package\n",
"Tymoteusz Wołodźko\n",
"\n",
"In this short notebook, I am going to present automatic hyperparameter tuning using the `hyperopt` Python package. As an example, we are going to tune the parameters for the Prophet time-series forecasting model."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"\n",
"import hyperopt\n",
"from hyperopt import fmin, tpe, rand, hp, Trials, STATUS_OK\n",
"\n",
"from fbprophet import Prophet\n",
"\n",
"# silence the messages\n",
"import logging\n",
"logging.getLogger('fbprophet').setLevel(logging.WARNING)\n",
"logging.getLogger('hyperopt').setLevel(logging.WARNING)\n",
"\n",
"import matplotlib.pyplot as plt\n",
"%matplotlib inline"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Data\n",
"\n",
"We are going to use data example of daily hires for Santander bikes over a period of approximately seven years that was alredy used in [this Prophet tutorial](https://cambridgespark.com/content/tutorials/prophet/index.html)."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Day</th>\n",
" <th>Number of Bicycle Hires</th>\n",
" <th>Unnamed: 2</th>\n",
" <th>Month</th>\n",
" <th>Number of Bicycle Hires.1</th>\n",
" <th>Unnamed: 5</th>\n",
" <th>Year</th>\n",
" <th>Number of Bicycle Hires.2</th>\n",
" <th>Unnamed: 8</th>\n",
" <th>Month.1</th>\n",
" <th>Average Hire Time (mins)</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2010-07-30</td>\n",
" <td>6897</td>\n",
" <td>NaN</td>\n",
" <td>2010-07-01</td>\n",
" <td>12461.0</td>\n",
" <td>NaN</td>\n",
" <td>2010</td>\n",
" <td>2180813</td>\n",
" <td>NaN</td>\n",
" <td>2010-07-01</td>\n",
" <td>17.232566</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2010-07-31</td>\n",
" <td>5564</td>\n",
" <td>NaN</td>\n",
" <td>2010-08-01</td>\n",
" <td>341203.0</td>\n",
" <td>NaN</td>\n",
" <td>2011</td>\n",
" <td>7142449</td>\n",
" <td>NaN</td>\n",
" <td>2010-08-01</td>\n",
" <td>16.551880</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2010-08-01</td>\n",
" <td>4303</td>\n",
" <td>NaN</td>\n",
" <td>2010-09-01</td>\n",
" <td>540859.0</td>\n",
" <td>NaN</td>\n",
" <td>2012</td>\n",
" <td>9519283</td>\n",
" <td>NaN</td>\n",
" <td>2010-09-01</td>\n",
" <td>15.219079</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2010-08-02</td>\n",
" <td>6642</td>\n",
" <td>NaN</td>\n",
" <td>2010-10-01</td>\n",
" <td>544412.0</td>\n",
" <td>NaN</td>\n",
" <td>2013</td>\n",
" <td>8045459</td>\n",
" <td>NaN</td>\n",
" <td>2010-10-01</td>\n",
" <td>15.204481</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2010-08-03</td>\n",
" <td>7966</td>\n",
" <td>NaN</td>\n",
" <td>2010-11-01</td>\n",
" <td>456304.0</td>\n",
" <td>NaN</td>\n",
" <td>2014</td>\n",
" <td>10023897</td>\n",
" <td>NaN</td>\n",
" <td>2010-11-01</td>\n",
" <td>13.776083</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Day Number of Bicycle Hires Unnamed: 2 Month \\\n",
"0 2010-07-30 6897 NaN 2010-07-01 \n",
"1 2010-07-31 5564 NaN 2010-08-01 \n",
"2 2010-08-01 4303 NaN 2010-09-01 \n",
"3 2010-08-02 6642 NaN 2010-10-01 \n",
"4 2010-08-03 7966 NaN 2010-11-01 \n",
"\n",
" Number of Bicycle Hires.1 Unnamed: 5 Year Number of Bicycle Hires.2 \\\n",
"0 12461.0 NaN 2010 2180813 \n",
"1 341203.0 NaN 2011 7142449 \n",
"2 540859.0 NaN 2012 9519283 \n",
"3 544412.0 NaN 2013 8045459 \n",
"4 456304.0 NaN 2014 10023897 \n",
"\n",
" Unnamed: 8 Month.1 Average Hire Time (mins) \n",
"0 NaN 2010-07-01 17.232566 \n",
"1 NaN 2010-08-01 16.551880 \n",
"2 NaN 2010-09-01 15.219079 \n",
"3 NaN 2010-10-01 15.204481 \n",
"4 NaN 2010-11-01 13.776083 "
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import os\n",
"from urllib.request import urlretrieve\n",
"\n",
"data_url = 'https://data.london.gov.uk/download/number-bicycle-hires/ac29363e-e0cb-47cc-a97a-e216d900a6b0/tfl-daily-cycle-hires.xls'\n",
"filename = data_url.split('/')[-1]\n",
"\n",
"if not os.path.isfile(filename):\n",
" # download the data once\n",
" urlretrieve (data_url, filename)\n",
"\n",
"dat = pd.read_excel(filename, sheet_name='Data')\n",
"dat.head()"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"dat = dat.rename(columns={'Day': 'ds', 'Number of Bicycle Hires': 'y'}) \n",
"dat = dat.loc[:, ['ds', 'y']]"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot( dat['ds'], dat['y'])\n",
"plt.xlabel('Date')\n",
"plt.ylabel('Number of cycle hires')\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Prophet time-series forecasting model & `fbprophet` package\n",
"\n",
"For forecasting, we are going to use [Prophet](https://research.fb.com/prophet-forecasting-at-scale/) model from the `fbprophet` package by Facebook ([Taylor & Letham, 2017](https://peerj.com/preprints/3190/)). The model has three main components: $g(t)$ [trend with changepoints](https://facebook.github.io/prophet/docs/trend_changepoints.html), $s(t)$ [periodic changes](https://facebook.github.io/prophet/docs/seasonality,_holiday_effects,_and_regressors.html) (e.g. weekly and yearly seasonality), $h(t)$ additional regressors (e.g. holiday and event dummies), and $\\varepsilon_t$ error term:\n",
"\n",
"$$\n",
"y_t = g(t) + s(t) + h(t) + \\varepsilon_t\n",
"$$\n",
"\n",
"The model is defined in Bayesian paradigm, where [Stan](http://mc-stan.org/) is used for estimating the parameters and sampling from posterior distribution using MCMC simulation. Since using Bayesian model, the parameters are assigned prior distribution, where the scale of the prior distributions play a role of regularization parameters. There are \"build-in\" methods for hyperparameter tuning for Bayesian models like using hyperpriors (priors over the hyperparameters themselves), but here we are going to use Prophet as a black-box model.\n",
"\n",
"The `Prophet` class has multiple parameters, but we are going to optimize only the *changepoint_prior_scale*, hyperparameter and the seasonality components (as conditional parameters). The [*uncertainty_samples* and *mcmc_samples*](https://facebook.github.io/prophet/docs/uncertainty_intervals.html) are set to zero to speed up the computation. The seasonalities are added to the model using `add_seasonality` method. `Prophet` class has following hyper parameters (excerpt from the docs, some parameters not included):\n",
"\n",
" growth: String 'linear' or 'logistic' to specify a linear or logistic\n",
" trend.\n",
" n_changepoints: Number of potential changepoints to include. Not used\n",
" if input `changepoints` is supplied. If `changepoints` is not supplied,\n",
" then n_changepoints potential changepoints are selected uniformly from\n",
" the first 80 percent of the history.\n",
" yearly_seasonality: Fit yearly seasonality.\n",
" Can be 'auto', True, False, or a number of Fourier terms to generate.\n",
" weekly_seasonality: Fit weekly seasonality.\n",
" Can be 'auto', True, False, or a number of Fourier terms to generate.\n",
" daily_seasonality: Fit daily seasonality.\n",
" Can be 'auto', True, False, or a number of Fourier terms to generate.\n",
" seasonality_prior_scale: Parameter modulating the strength of the\n",
" seasonality model. Larger values allow the model to fit larger seasonal\n",
" fluctuations, smaller values dampen the seasonality. Can be specified\n",
" for individual seasonalities using add_seasonality.\n",
" changepoint_prior_scale: Parameter modulating the flexibility of the\n",
" automatic changepoint selection. Large values will allow many\n",
" changepoints, small values will allow few changepoints.\n",
"\n",
"Below, we define the `estimator` function that generates the Prophet class object that can be used for fitting the model and making predictions. The `estimator` function takes as input a dict of parameters, where the Prophet defaults are:"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"default_params = {\n",
" 'changepoint_prior_scale' : 0.05,\n",
" 'daily' : { 'fourier_order' : 4, 'prior_scale' : 10 }, # included if feasible\n",
" 'weekly' : { 'fourier_order' : 3, 'prior_scale' : 10 }, # included if feasible\n",
" 'yearly' : { 'fourier_order' : 10, 'prior_scale' : 10 } # included if feasible\n",
"}"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The seasonal components can be omitted in `estimator` by not including them, or setting them to `False`."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"def estimator(params, uncertainty_samples=0, mcmc_samples=0):\n",
" \n",
" periods = { 'daily' : 1, 'weekly' : 7, 'yearly' : 365.25 }\n",
" \n",
" proph = Prophet(growth='linear', n_changepoints=25,\n",
" changepoint_prior_scale=params['changepoint_prior_scale'],\n",
" uncertainty_samples=uncertainty_samples, mcmc_samples=mcmc_samples)\n",
" \n",
" for kind in ['daily', 'weekly', 'yearly']:\n",
" try:\n",
" if params[kind]:\n",
" proph.add_seasonality(name=kind,\n",
" period=periods[kind],\n",
" fourier_order=int(params[kind]['fourier_order']),\n",
" prior_scale=params[kind]['prior_scale'])\n",
" except KeyError:\n",
" pass\n",
" \n",
" return proph"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"First, we fit the Prophet model using default settings to obtain a simple benchmark. The default settings usually would give a reasonably well solution."
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/usr/local/lib/python3.5/dist-packages/pystan/misc.py:399: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
" elif np.issubdtype(np.asarray(v).dtype, float):\n"
]
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 720x432 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"proph = estimator(default_params)\n",
"proph.fit(dat)\n",
"\n",
"df_dates = proph.make_future_dataframe(periods=365, include_history=True)\n",
"\n",
"model_predictions = proph.predict( df_dates )\n",
"proph.plot( model_predictions )\n",
"plt.legend(loc='best', fontsize=20)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"29428353.16934275"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# mean squared error metric\n",
"mse = lambda y, yhat : np.mean((y-yhat)**2)\n",
"\n",
"predicted = proph.predict(dat)['yhat']\n",
"\n",
"mse(dat['y'], predicted)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Cross-validation\n",
"\n",
"To assess the forecast we are going to use the [time-series cross validation](https://otexts.org/fpp2/accuracy.html) (Hyndman and Athanasopoulos, 2018):\n",
"\n",
" In this procedure, there are a series of test sets, each consisting of a single observation. The corresponding training set consists only of observations that occurred prior to the observation that forms the test set. Thus, no future observations can be used in constructing the forecast. Since it is not possible to obtain a reliable forecast based on a small training set, the earliest observations are not considered as test sets.\n",
"\n",
" The following diagram illustrates the series of training and test sets, where the blue observations form the training sets, and the red observations form the test sets.\n",
"\n",
"![](https://otexts.org/fpp2/fpp_files/figure-html/cv1-1.png)\n",
"\n",
"For this, we define the `train_test_split` function that uses the first *1,2,...,n* years as a training set and *n+1* year as a test set."
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"def train_test_split(test_start_year=2017):\n",
" \n",
" test_start = str(test_start_year) + '-01-01'\n",
" test_end = str(test_start_year + 1) + '-01-01'\n",
" \n",
" train = dat.loc[(dat.ds < test_start), :]\n",
" test = dat.loc[(dat.ds >= test_start) & (dat.ds < test_end), :]\n",
" \n",
" return train, test"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Function to optimize\n",
"\n",
"The `train_test` is a black-box function to optimize. It takes as an input a dict of parameters, so to define a model using the `estimator` function, fit it, make predictions on test set and compare the predictions using *mean squared error* metric. The model is re-fitted three times and evaluated for the three test sets, then the errors are averaged."
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/usr/local/lib/python3.5/dist-packages/pystan/misc.py:399: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
" elif np.issubdtype(np.asarray(v).dtype, float):\n"
]
},
{
"data": {
"text/plain": [
"47238442.14777574"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"def train_test(params):\n",
" \n",
" def single_step(train, test):\n",
" \n",
" forecast_window = test.shape[0]\n",
" \n",
" proph = estimator(params)\n",
" proph.fit(train)\n",
" \n",
" future = proph.make_future_dataframe(periods=forecast_window).tail(forecast_window)\n",
" predicted = proph.predict(future)['yhat']\n",
" \n",
" return mse(test['y'].values, predicted)\n",
" \n",
" tmp_err = []\n",
" \n",
" for year in [2015, 2016, 2017]:\n",
" \n",
" train, test = train_test_split(year)\n",
" \n",
" tmp_err.append(single_step(train, test))\n",
" \n",
" return {\n",
" 'loss' : np.mean(tmp_err),\n",
" 'status' : STATUS_OK,\n",
" 'space' : params\n",
" }\n",
"\n",
"mse_default = train_test(default_params)['loss']\n",
"mse_default"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## The `hyperopt` package\n",
"\n",
"[`hyperopt`](http://hyperopt.github.io/hyperopt/) package was [presented on the SciPy 2013 conference](https://www.youtube.com/watch?v=Mp1xnPfE4PY) (see Bergstra et al, [2013](https://conference.scipy.org/proceedings/scipy2013/pdfs/bergstra_hyperopt.pdf), [2015](http://iopscience.iop.org/article/10.1088/1749-4699/8/1/014008/ampdf)). It has [nice documentation](https://github.com/hyperopt/hyperopt/wiki/FMin), moreover additional information can be found in two posts by [Vooban](https://medium.com/vooban-ai/hyperopt-tutorial-for-optimizing-neural-networks-hyperparameters-e3102814b919) and [FastML](http://fastml.com/optimizing-hyperparams-with-hyperopt/). The package allows for hyperparameter tuning using *Tree-structured Parzen Estimator (TPE) algorithm* (see Bergstra et al, [2011](https://www.semanticscholar.org/paper/Algorithms-for-Hyper-Parameter-Optimization-Bergstra-Bardenet/9f2aefc3821853e963beda011ed770f740385b77), [2013](http://proceedings.mlr.press/v28/bergstra13.pdf)). To read more on hyperparameter tuning see [this great article](http://neupy.com/2016/12/17/hyperparameter_optimization_for_neural_networks.html).\n",
"\n",
"### Search space for parameters\n",
"\n",
"`hyperopt` needs us to define the search space for parameters with a tuple or dict defining the prior *distributions* of parameters. The most basic choices are continuous uniform distributions (`hp.uniform`) for continuous parameters, discrete uniform (`hp.randint`) for integer-valued parameters, and `hp.choice` for arbitrary-valued parameters. Moreover, `hp.choice` can be used for *conditional parameters*."
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'changepoint_prior_scale': 4.738162591055831,\n",
" 'daily': False,\n",
" 'weekly': False,\n",
" 'yearly': {'fourier_order': 19, 'prior_scale': 27.261869987725817}}"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"param_space = {\n",
" 'changepoint_prior_scale' : hp.uniform('changepoint_prior_scale', low=0, high=5),\n",
" 'daily' : hp.choice('daily', [\n",
" False,\n",
" {\n",
" 'fourier_order' : 1 + hp.randint('daily_fourier_order', upper=4*3),\n",
" 'prior_scale' : hp.uniform('daily_prior_scale', low=0, high=50)\n",
" }\n",
" ]),\n",
" 'weekly' : hp.choice('weekly', [\n",
" False ,\n",
" {\n",
" 'fourier_order' : 1 + hp.randint('weekly_fourier_order', upper=3*3),\n",
" 'prior_scale' : hp.uniform('weekly_prior_scale', low=0, high=50)\n",
" }\n",
" ]),\n",
" 'yearly' : hp.choice('yearly', [\n",
" False,\n",
" {\n",
" 'fourier_order' : 1 + hp.randint('yearly_fourier_order', upper=10*3),\n",
" 'prior_scale' : hp.uniform('yearly_prior_scale', low=0, high=50)\n",
" }\n",
" ]),\n",
"}\n",
"\n",
"hyperopt.pyll.stochastic.sample(param_space)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Alternatively, we may use non-uniform distributions for parameters, e.g. log-uniform (`hp.loguniform`), log-normal (`hp.lognormal`), or discretized log-normal (`hp.qloguniform`) for integer-valued parameters. Several other distributions [are also supported](https://github.com/hyperopt/hyperopt/wiki/FMin). Below, we are going to use log-uniform distribution for *changepoint_prior_scale*; `hp.qloguniform` for *daily_fourier_order*, where the upper level is equal to three times greater then the Prophet default; log-normal distribution with mean equal to Prophet defaults and standard deviation equal to one. By choosing skewed distributions, we make the optimizer more focused on the smaller values of the parameters."
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 4 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from collections import Counter\n",
"\n",
"logunif = lambda low, high : np.exp(np.random.uniform(size=50000, low=low, high=high))\n",
"qlogunif = lambda low, high, q : np.round(np.exp(np.random.uniform(size=50000, low=low, high=high)) / q) * q\n",
"lognorm = lambda mu, sigma : np.exp(np.random.normal(size=50000, loc=mu, scale=sigma))\n",
"lognorm = lambda mu, sigma : np.exp(np.random.normal(size=50000, loc=mu, scale=sigma))\n",
"\n",
"\n",
"fig, axes = plt.subplots(nrows=2, ncols=2)\n",
"fig.tight_layout()\n",
"\n",
"plt.subplot(2, 2, 1)\n",
"\n",
"x = logunif(low=0, high=np.log(6)) - 1\n",
"\n",
"plt.hist(x, bins=100)\n",
"plt.title(\"log-uniform bounded in $[0,\\\\; 5]$\")\n",
"\n",
"plt.subplot(2, 2, 2)\n",
"\n",
"x = qlogunif(low=0, high=np.log(10*3), q=1)\n",
"\n",
"hst = Counter(x)\n",
"\n",
"plt.plot(hst.keys(), hst.values(), 'bo', ms=2)\n",
"plt.vlines(hst.keys(), 0, hst.values(), colors='b', lw=1, alpha=0.5)\n",
"plt.title(\"q-log-uniform bounded in $[1,\\\\; 10 \\\\times 3]$\")\n",
"\n",
"plt.subplot(2, 2, 3)\n",
"\n",
"x = lognorm(mu=np.log(3)-0.5, sigma=1)\n",
"\n",
"plt.hist(x, bins=100)\n",
"plt.title(\"log-normal with $\\mu = 3$\")\n",
"\n",
"plt.subplot(2, 2, 4)\n",
"\n",
"x = lognorm(mu=np.log(10)-0.5, sigma=1)\n",
"\n",
"plt.hist(x, bins=100)\n",
"plt.title(\"log-normal with $\\mu = 10$\")\n",
"\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'changepoint_prior_scale': 2.863260055247223,\n",
" 'daily': {'fourier_order': 4.0, 'prior_scale': 11.09348189815281},\n",
" 'weekly': {'fourier_order': 1.0, 'prior_scale': 6.288469466534371},\n",
" 'yearly': {'fourier_order': 2.0, 'prior_scale': 1.8976815479274791}}"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"param_space = {\n",
" 'changepoint_prior_scale' : hp.loguniform('changepoint_prior_scale', low=0, high=np.log(6)) - 1,\n",
" 'daily' : hp.choice('daily', [\n",
" False,\n",
" {\n",
" 'fourier_order' : hp.qloguniform('daily_fourier_order', low=0, high=np.log(4*3), q=1),\n",
" 'prior_scale' : hp.lognormal('daily_prior_scale', mu=np.log(10)-0.5, sigma=1)\n",
" }\n",
" ]),\n",
" 'weekly' : hp.choice('weekly', [\n",
" False ,\n",
" {\n",
" 'fourier_order' : hp.qloguniform('weekly_fourier_order', low=0, high=np.log(3*3), q=1),\n",
" 'prior_scale' : hp.lognormal('weekly_prior_scale', mu=np.log(10)-0.5, sigma=1)\n",
" }\n",
" ]),\n",
" 'yearly' : hp.choice('yearly', [\n",
" False,\n",
" {\n",
" 'fourier_order' : hp.qloguniform('yearly_fourier_order', low=0, high=np.log(10*3), q=1),\n",
" 'prior_scale' : hp.lognormal('yearly_prior_scale', mu=np.log(10)-0.5, sigma=1)\n",
" }\n",
" ]),\n",
"}\n",
"\n",
"# obtain a single sample as a sanity check\n",
"hyperopt.pyll.stochastic.sample(param_space)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Optimization using `fmin`\n",
"\n",
"Now we can use the `fmin` function to find the minimum of our `opt_func` function. The parameter search space is defined by the *space* argument, *algo=tpe.suggest* tells the optimizer to use *Tree-structured Parzen Estimator* (alternatively we can use: `random.suggest` for random search, or `anneal.suggest` for annealing). The optimizer will run for *max_evals* number of iterations.\n",
"\n",
"Additionally, we use the `Trails` class object that will record the metadata for intermediate optimization steps.\n",
"\n",
"Since `fmin` does not have any progress bar and instead it uses noisy stdout messages (that we already turned off), first we are going to define a `tqdm_progress_bar` [decorator](https://www.thecodeship.com/patterns/guide-to-python-function-decorators/) that will add the `tqdm` progress bar to our `train_test` function."
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"# using global progress bar as suggested in:\n",
"# https://github.com/hyperopt/hyperopt/issues/392\n",
"\n",
"from tqdm import tqdm\n",
"\n",
"def tqdm_progress_bar(iters):\n",
" \n",
" global pbar\n",
" pbar = tqdm(total=iters)\n",
" \n",
" def decorator(func):\n",
" def wrapper(*args, **kwargs):\n",
" pbar.update()\n",
" return func(*args, **kwargs)\n",
" return wrapper\n",
" \n",
" return decorator"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
" 0%| | 0/50 [00:00<?, ?it/s]/usr/local/lib/python3.5/dist-packages/pystan/misc.py:399: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
" elif np.issubdtype(np.asarray(v).dtype, float):\n",
"100%|██████████| 50/50 [08:13<00:00, 10.30s/it]"
]
},
{
"data": {
"text/plain": [
"{'changepoint_prior_scale': 4.959074003513106,\n",
" 'daily': {'fourier_order': 2.0, 'prior_scale': 12.039048576134826},\n",
" 'weekly': {'fourier_order': 4.0, 'prior_scale': 2.024431438109962},\n",
" 'yearly': {'fourier_order': 3.0, 'prior_scale': 108.30049721858441}}"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"MAX_EVALS = 50\n",
"\n",
"@tqdm_progress_bar(MAX_EVALS)\n",
"def opt_func(params):\n",
" return train_test(params)\n",
"\n",
"trials = Trials()\n",
"\n",
"best = fmin(fn=opt_func, space=param_space, algo=tpe.suggest, trials=trials, max_evals=MAX_EVALS)\n",
"\n",
"# transform the parameters to the same format as input format of search space\n",
"best_params = hyperopt.space_eval(param_space, best)\n",
"best_params"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(np.minimum.accumulate(trials.losses()), lw=1, label='best fit')\n",
"plt.plot(trials.losses(), ls=':', label='intermediate losses')\n",
"\n",
"plt.axhline(y=mse_default, ls='--', lw=1, color='red', label='baseline')\n",
"\n",
"# Show if seasonality components were included\n",
"plt.plot(5.7e+7 * np.array([bool(t['result']['space']['daily']) for t in trials.trials]), 'o', label='daily')\n",
"plt.plot(5.5e+7 * np.array([bool(t['result']['space']['weekly']) for t in trials.trials]), 'o', label='weekly')\n",
"plt.plot(5.3e+7 * np.array([bool(t['result']['space']['yearly']) for t in trials.trials]), 'o', label='yearly')\n",
"\n",
"plt.legend(loc='upper center', ncol=3)\n",
"\n",
"plt.title('Optimization progress')\n",
"plt.ylim((2.5e+7, 7e+7))\n",
"\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/usr/local/lib/python3.5/dist-packages/pystan/misc.py:399: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
" elif np.issubdtype(np.asarray(v).dtype, float):\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x432 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"proph = estimator(best_params, uncertainty_samples=500)\n",
"proph.fit(dat)\n",
"\n",
"df_dates = proph.make_future_dataframe(periods=365, include_history=True)\n",
"\n",
"model_predictions = proph.predict( df_dates )\n",
"proph.plot( model_predictions )\n",
"plt.legend(loc='best', fontsize=20)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Last update: 2018-08-01 16:01:43.756932\n"
]
}
],
"source": [
"import datetime\n",
"print('Last update:', datetime.datetime.now())"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.5.2"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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