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[Doc] Added HierE2E Favorita baseline #217

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merged 16 commits into from
Jun 26, 2023
Merged

[Doc] Added HierE2E Favorita baseline #217

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145a18d
First iteration of HierE2E execution
kdgutier Jun 15, 2023
ed78664
Corrected HierE2E pipeline
kdgutier Jun 16, 2023
9800f66
Added relMSE and MSSE evaluation
kdgutier Jun 16, 2023
a1109b5
Added relMSE and MSSE evaluation
kdgutier Jun 16, 2023
c1bd049
Merge branch 'main' into doc/run_baselines2
cchallu Jun 21, 2023
92eea83
Merge branch 'main' of ssh://github.com/Nixtla/hierarchicalforecast i…
kdgutier Jun 21, 2023
735fcba
Added note on available methods and predict_insample methods
kdgutier Jun 21, 2023
8bdb7d0
Merge branch 'doc/run_baselines2' of ssh://github.com/Nixtla/hierarch…
kdgutier Jun 21, 2023
9075120
Installed hooks and cleaned notebook
kdgutier Jun 21, 2023
ae5fffb
Fixed missing favicon
kdgutier Jun 21, 2023
dc946b0
Fixed broken Getting Started quarto link
kdgutier Jun 21, 2023
5dbdebc
Favorita's HierE2E, implied composite likelihood approach
kdgutier Jun 21, 2023
23ee230
Favorita's HierE2E, implied composite likelihood approach
kdgutier Jun 21, 2023
2034b8d
Favorita's HierE2E, implied composite likelihood approach
kdgutier Jun 22, 2023
bbafe52
Favorita's HierE2E, implied composite likelihood approach
kdgutier Jun 22, 2023
725346b
Fix merge conflict
kdgutier Jun 22, 2023
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84 changes: 59 additions & 25 deletions experiments/hierarchical_baselines/nbs/run_favorita_baselines.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -20,16 +20,7 @@
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/kin/anaconda3/envs/hierarchical_baselines/lib/python3.10/site-packages/statsforecast/core.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
" from tqdm.autonotebook import tqdm\n"
]
}
],
"outputs": [],
"source": [
"import os\n",
"import argparse\n",
Expand All @@ -41,21 +32,30 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"# %%capture\n",
"# !pip install statsforecast\n",
"# !pip install hierarchicalforecast\n",
"# !pip install git+https://github.com/Nixtla/datasetsforecast@feat/favorita_dataset.git"
"# !pip install git+https://github.com/Nixtla/datasetsforecast.git@feat/favorita_dataset"
]
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 3,
"metadata": {},
"outputs": [],
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/kin/anaconda3/envs/hierarchical_baselines/lib/python3.10/site-packages/statsforecast/core.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
" from tqdm.autonotebook import tqdm\n"
]
}
],
"source": [
"from statsforecast.core import StatsForecast\n",
"from statsforecast.models import AutoARIMA, Naive\n",
Expand All @@ -77,7 +77,7 @@
},
{
"cell_type": "code",
"execution_count": 2,
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
Expand Down Expand Up @@ -166,16 +166,50 @@
},
{
"cell_type": "code",
"execution_count": 3,
"execution_count": 5,
"metadata": {},
"outputs": [],
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"100%|██████████| 930M/930M [00:21<00:00, 43.4MiB/s] \n",
"INFO:datasetsforecast.utils:Successfully downloaded favorita-grocery-sales-forecasting2.zip, 930159981, bytes.\n",
"INFO:datasetsforecast.utils:Decompressing zip file...\n",
"INFO:datasetsforecast.utils:Successfully decompressed data/favorita/favorita-grocery-sales-forecasting2.zip\n",
"INFO:datasetsforecast.utils:Decompressing zip file...\n",
"INFO:datasetsforecast.utils:Successfully decompressed data/favorita/holidays_events.csv.zip\n",
"INFO:datasetsforecast.utils:Decompressing zip file...\n",
"INFO:datasetsforecast.utils:Successfully decompressed data/favorita/items.csv.zip\n",
"INFO:datasetsforecast.utils:Decompressing zip file...\n",
"INFO:datasetsforecast.utils:Successfully decompressed data/favorita/oil.csv.zip\n",
"INFO:datasetsforecast.utils:Decompressing zip file...\n",
"INFO:datasetsforecast.utils:Successfully decompressed data/favorita/sample_submission.csv.zip\n",
"INFO:datasetsforecast.utils:Decompressing zip file...\n",
"INFO:datasetsforecast.utils:Successfully decompressed data/favorita/stores.csv.zip\n",
"INFO:datasetsforecast.utils:Decompressing zip file...\n",
"INFO:datasetsforecast.utils:Successfully decompressed data/favorita/test.csv.zip\n",
"INFO:datasetsforecast.utils:Decompressing zip file...\n",
"INFO:datasetsforecast.utils:Successfully decompressed data/favorita/train.csv.zip\n",
"INFO:datasetsforecast.utils:Decompressing zip file...\n",
"INFO:datasetsforecast.utils:Successfully decompressed data/favorita/transactions.csv.zip\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"saved train.csv to train.feather for fast access\n"
]
}
],
"source": [
"data = FavoritaHierarchicalDataset.load_item_data(item_id=1916577, directory = './data/favorita', dataset='Favorita200')"
]
},
{
"cell_type": "code",
"execution_count": 4,
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
Expand Down Expand Up @@ -280,7 +314,7 @@
},
{
"cell_type": "code",
"execution_count": 5,
"execution_count": 7,
"metadata": {},
"outputs": [
{
Expand All @@ -293,16 +327,16 @@
"\n",
"Favorita200 item_id=112830, h=34 n_series=93, n_bottom=54 \n",
"test ds=[(Timestamp('2017-07-13 00:00:00'), Timestamp('2017-08-15 00:00:00'))] \n",
"Code block 'Read and Parse data ' took:\t0.56446 seconds\n",
"Code block 'Fit/Predict Model\t ' took:\t0.13728 seconds\n",
"Code block 'Reconcile Predictions ' took:\t35.96450 seconds\n",
"Code block 'Read and Parse data ' took:\t0.60365 seconds\n",
"Code block 'Fit/Predict Model\t ' took:\t30.04792 seconds\n",
"Code block 'Reconcile Predictions ' took:\t38.54011 seconds\n",
"\n",
"\n",
"Favorita200 item_id=1916577, h=34 n_series=93, n_bottom=54 \n",
"test ds=[(Timestamp('2017-07-13 00:00:00'), Timestamp('2017-08-15 00:00:00'))] \n",
"Code block 'Read and Parse data ' took:\t0.58135 seconds\n",
"Code block 'Fit/Predict Model\t ' took:\t0.12099 seconds\n",
"Code block 'Reconcile Predictions ' took:\t35.64888 seconds\n",
"Code block 'Read and Parse data ' took:\t0.61150 seconds\n",
"Code block 'Fit/Predict Model\t ' took:\t29.67945 seconds\n",
"Code block 'Reconcile Predictions ' took:\t38.78811 seconds\n",
"\n",
"\n"
]
Expand Down
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