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ray/doc/source/ray-air/examples/xgboost_example.ipynb

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{
"cells": [
{
"cell_type": "markdown",
"id": "5fb89b3d",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"# Training a model with distributed XGBoost\n",
"In this example we will train a model in Ray AIR using distributed XGBoost."
]
},
{
"cell_type": "markdown",
"id": "53d57c1f",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Let's start with installing our dependencies:"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "41f20cc1",
"metadata": {
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"!pip install -qU \"ray[tune]\" xgboost_ray"
]
},
{
"cell_type": "markdown",
"id": "d2fe8d4a",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Then we need some imports:"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "7232303d",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/ubuntu/ray/venv/lib/python3.8/site-packages/xgboost/compat.py:31: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
" from pandas import MultiIndex, Int64Index\n",
"FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"FutureWarning: pandas.Float64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"FutureWarning: pandas.UInt64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n"
]
}
],
"source": [
"from typing import Tuple\n",
"\n",
"import ray\n",
"from ray.train.batch_predictor import BatchPredictor\n",
"from ray.train.xgboost import XGBoostPredictor\n",
"from ray.train.xgboost import XGBoostTrainer\n",
"from ray.air.config import ScalingConfig\n",
"from ray.data.dataset import Dataset\n",
"from ray.air.result import Result\n",
"from ray.data.preprocessors import StandardScaler"
]
},
{
"cell_type": "markdown",
"id": "1c75b5ca",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Next we define a function to load our train, validation, and test datasets."
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "37c4f38f",
"metadata": {},
"outputs": [],
"source": [
"def prepare_data() -> Tuple[Dataset, Dataset, Dataset]:\n",
" dataset = ray.data.read_csv(\"s3://anonymous@air-example-data/breast_cancer.csv\")\n",
" train_dataset, valid_dataset = dataset.train_test_split(test_size=0.3)\n",
" test_dataset = valid_dataset.drop_columns([\"target\"])\n",
" return train_dataset, valid_dataset, test_dataset"
]
},
{
"cell_type": "markdown",
"id": "9b2850dd",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"The following function will create a XGBoost trainer, train it, and return the result."
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "dae8998d",
"metadata": {
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"def train_xgboost(num_workers: int, use_gpu: bool = False) -> Result:\n",
" train_dataset, valid_dataset, _ = prepare_data()\n",
"\n",
" # Scale some random columns\n",
" columns_to_scale = [\"mean radius\", \"mean texture\"]\n",
" preprocessor = StandardScaler(columns=columns_to_scale)\n",
"\n",
" # XGBoost specific params\n",
" params = {\n",
" \"tree_method\": \"approx\",\n",
" \"objective\": \"binary:logistic\",\n",
" \"eval_metric\": [\"logloss\", \"error\"],\n",
" }\n",
"\n",
" trainer = XGBoostTrainer(\n",
" scaling_config=ScalingConfig(num_workers=num_workers, use_gpu=use_gpu),\n",
" label_column=\"target\",\n",
" params=params,\n",
" datasets={\"train\": train_dataset, \"valid\": valid_dataset},\n",
" preprocessor=preprocessor,\n",
" num_boost_round=100,\n",
" )\n",
" result = trainer.fit()\n",
" print(result.metrics)\n",
"\n",
" return result"
]
},
{
"cell_type": "markdown",
"id": "ce05af87",
"metadata": {},
"source": [
"Once we have the result, we can do batch inference on the obtained model. Let's define a utility function for this."
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "5b8076d3",
"metadata": {
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [],
"source": [
"def predict_xgboost(result: Result):\n",
" _, _, test_dataset = prepare_data()\n",
"\n",
" batch_predictor = BatchPredictor.from_checkpoint(\n",
" result.checkpoint, XGBoostPredictor\n",
" )\n",
"\n",
" predicted_labels = (\n",
" batch_predictor.predict(test_dataset)\n",
" .map_batches(lambda df: (df > 0.5).astype(int), batch_format=\"pandas\")\n",
" )\n",
" print(f\"PREDICTED LABELS\")\n",
" predicted_labels.show()\n",
"\n",
" shap_values = batch_predictor.predict(test_dataset, pred_contribs=True)\n",
" print(f\"SHAP VALUES\")\n",
" shap_values.show()\n"
]
},
{
"cell_type": "markdown",
"id": "7e172f66",
"metadata": {},
"source": [
"Now we can run the training:"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "0f96d62b",
"metadata": {
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"2022-06-22 17:28:55,841\tINFO services.py:1477 -- View the Ray dashboard at \u001b[1m\u001b[32mhttp://127.0.0.1:8270\u001b[39m\u001b[22m\n",
"2022-06-22 17:28:58,044\tWARNING read_api.py:260 -- The number of blocks in this dataset (1) limits its parallelism to 1 concurrent tasks. This is much less than the number of available CPU slots in the cluster. Use `.repartition(n)` to increase the number of dataset blocks.\n",
"Map_Batches: 100%|██████████| 1/1 [00:00<00:00, 40.28it/s]\n"
]
},
{
"data": {
"text/html": [
"== Status ==<br>Current time: 2022-06-22 17:29:15 (running for 00:00:16.11)<br>Memory usage on this node: 11.5/31.0 GiB<br>Using FIFO scheduling algorithm.<br>Resources requested: 0/8 CPUs, 0/0 GPUs, 0.0/12.35 GiB heap, 0.0/6.18 GiB objects<br>Result logdir: /home/ubuntu/ray_results/XGBoostTrainer_2022-06-22_17-28-58<br>Number of trials: 1/1 (1 TERMINATED)<br><table>\n",
"<thead>\n",
"<tr><th>Trial name </th><th>status </th><th>loc </th><th style=\"text-align: right;\"> iter</th><th style=\"text-align: right;\"> total time (s)</th><th style=\"text-align: right;\"> train-logloss</th><th style=\"text-align: right;\"> train-error</th><th style=\"text-align: right;\"> valid-logloss</th></tr>\n",
"</thead>\n",
"<tbody>\n",
"<tr><td>XGBoostTrainer_cc863_00000</td><td>TERMINATED</td><td>172.31.43.110:1493910</td><td style=\"text-align: right;\"> 100</td><td style=\"text-align: right;\"> 12.5164</td><td style=\"text-align: right;\"> 0.005874</td><td style=\"text-align: right;\"> 0</td><td style=\"text-align: right;\"> 0.078188</td></tr>\n",
"</tbody>\n",
"</table><br><br>"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\u001b[2m\u001b[36m(pid=1493910)\u001b[0m /home/ubuntu/ray/venv/lib/python3.8/site-packages/xgboost/compat.py:31: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"\u001b[2m\u001b[36m(pid=1493910)\u001b[0m from pandas import MultiIndex, Int64Index\n",
"\u001b[2m\u001b[36m(pid=1493910)\u001b[0m FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"\u001b[2m\u001b[36m(pid=1493910)\u001b[0m FutureWarning: pandas.Float64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"\u001b[2m\u001b[36m(pid=1493910)\u001b[0m FutureWarning: pandas.UInt64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"\u001b[2m\u001b[36m(XGBoostTrainer pid=1493910)\u001b[0m UserWarning: Dataset 'train' has 1 blocks, which is less than the `num_workers` 2. This dataset will be automatically repartitioned to 2 blocks.\n",
"\u001b[2m\u001b[36m(XGBoostTrainer pid=1493910)\u001b[0m UserWarning: Dataset 'valid' has 1 blocks, which is less than the `num_workers` 2. This dataset will be automatically repartitioned to 2 blocks.\n",
"\u001b[2m\u001b[36m(XGBoostTrainer pid=1493910)\u001b[0m 2022-06-22 17:29:04,073\tINFO main.py:980 -- [RayXGBoost] Created 2 new actors (2 total actors). Waiting until actors are ready for training.\n",
"\u001b[2m\u001b[36m(pid=1494007)\u001b[0m /home/ubuntu/ray/venv/lib/python3.8/site-packages/xgboost/compat.py:31: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"\u001b[2m\u001b[36m(pid=1494007)\u001b[0m from pandas import MultiIndex, Int64Index\n",
"\u001b[2m\u001b[36m(pid=1494008)\u001b[0m /home/ubuntu/ray/venv/lib/python3.8/site-packages/xgboost/compat.py:31: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"\u001b[2m\u001b[36m(pid=1494008)\u001b[0m from pandas import MultiIndex, Int64Index\n",
"\u001b[2m\u001b[36m(pid=1494009)\u001b[0m /home/ubuntu/ray/venv/lib/python3.8/site-packages/xgboost/compat.py:31: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"\u001b[2m\u001b[36m(pid=1494009)\u001b[0m from pandas import MultiIndex, Int64Index\n",
"\u001b[2m\u001b[36m(pid=1494007)\u001b[0m FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"\u001b[2m\u001b[36m(pid=1494007)\u001b[0m FutureWarning: pandas.Float64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"\u001b[2m\u001b[36m(pid=1494007)\u001b[0m FutureWarning: pandas.UInt64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"\u001b[2m\u001b[36m(pid=1494008)\u001b[0m FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"\u001b[2m\u001b[36m(pid=1494008)\u001b[0m FutureWarning: pandas.Float64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"\u001b[2m\u001b[36m(pid=1494008)\u001b[0m FutureWarning: pandas.UInt64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"\u001b[2m\u001b[36m(_RemoteRayXGBoostActor pid=1494008)\u001b[0m 2022-06-22 17:29:07,324\tWARNING __init__.py:190 -- DeprecationWarning: `ray.worker.get_resource_ids` is a private attribute and access will be removed in a future Ray version.\n",
"\u001b[2m\u001b[36m(pid=1494009)\u001b[0m FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"\u001b[2m\u001b[36m(pid=1494009)\u001b[0m FutureWarning: pandas.Float64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"\u001b[2m\u001b[36m(pid=1494009)\u001b[0m FutureWarning: pandas.UInt64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"\u001b[2m\u001b[36m(_RemoteRayXGBoostActor pid=1494009)\u001b[0m 2022-06-22 17:29:07,421\tWARNING __init__.py:190 -- DeprecationWarning: `ray.worker.get_resource_ids` is a private attribute and access will be removed in a future Ray version.\n",
"\u001b[2m\u001b[36m(XGBoostTrainer pid=1493910)\u001b[0m 2022-06-22 17:29:07,874\tINFO main.py:1025 -- [RayXGBoost] Starting XGBoost training.\n",
"\u001b[2m\u001b[36m(_RemoteRayXGBoostActor pid=1494008)\u001b[0m [17:29:07] task [xgboost.ray]:139731353900128 got new rank 0\n",
"\u001b[2m\u001b[36m(_RemoteRayXGBoostActor pid=1494008)\u001b[0m FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"\u001b[2m\u001b[36m(_RemoteRayXGBoostActor pid=1494009)\u001b[0m [17:29:07] task [xgboost.ray]:140076138558608 got new rank 1\n",
"\u001b[2m\u001b[36m(_RemoteRayXGBoostActor pid=1494009)\u001b[0m FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"\u001b[2m\u001b[36m(_QueueActor pid=1494006)\u001b[0m /home/ubuntu/ray/venv/lib/python3.8/site-packages/xgboost/compat.py:31: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"\u001b[2m\u001b[36m(_QueueActor pid=1494006)\u001b[0m from pandas import MultiIndex, Int64Index\n",
"\u001b[2m\u001b[36m(_QueueActor pid=1494006)\u001b[0m FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"\u001b[2m\u001b[36m(_QueueActor pid=1494006)\u001b[0m FutureWarning: pandas.Float64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"\u001b[2m\u001b[36m(_QueueActor pid=1494006)\u001b[0m FutureWarning: pandas.UInt64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Result for XGBoostTrainer_cc863_00000:\n",
" date: 2022-06-22_17-29-09\n",
" done: false\n",
" experiment_id: dc3dac01a34043cfb5751907e2bc648e\n",
" hostname: ip-172-31-43-110\n",
" iterations_since_restore: 1\n",
" node_ip: 172.31.43.110\n",
" pid: 1493910\n",
" should_checkpoint: true\n",
" time_since_restore: 7.967940330505371\n",
" time_this_iter_s: 7.967940330505371\n",
" time_total_s: 7.967940330505371\n",
" timestamp: 1655918949\n",
" timesteps_since_restore: 0\n",
" train-error: 0.017588\n",
" train-logloss: 0.464648\n",
" training_iteration: 1\n",
" trial_id: cc863_00000\n",
" valid-error: 0.081871\n",
" valid-logloss: 0.496374\n",
" warmup_time: 0.004768848419189453\n",
" \n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\u001b[2m\u001b[36m(XGBoostTrainer pid=1493910)\u001b[0m 2022-06-22 17:29:14,546\tINFO main.py:1516 -- [RayXGBoost] Finished XGBoost training on training data with total N=398 in 10.52 seconds (6.66 pure XGBoost training time).\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Result for XGBoostTrainer_cc863_00000:\n",
" date: 2022-06-22_17-29-14\n",
" done: true\n",
" experiment_id: dc3dac01a34043cfb5751907e2bc648e\n",
" experiment_tag: '0'\n",
" hostname: ip-172-31-43-110\n",
" iterations_since_restore: 100\n",
" node_ip: 172.31.43.110\n",
" pid: 1493910\n",
" should_checkpoint: true\n",
" time_since_restore: 12.516392230987549\n",
" time_this_iter_s: 0.03008890151977539\n",
" time_total_s: 12.516392230987549\n",
" timestamp: 1655918954\n",
" timesteps_since_restore: 0\n",
" train-error: 0.0\n",
" train-logloss: 0.005874\n",
" training_iteration: 100\n",
" trial_id: cc863_00000\n",
" valid-error: 0.040936\n",
" valid-logloss: 0.078188\n",
" warmup_time: 0.004768848419189453\n",
" \n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"2022-06-22 17:29:15,362\tINFO tune.py:734 -- Total run time: 16.94 seconds (16.08 seconds for the tuning loop).\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'train-logloss': 0.005874, 'train-error': 0.0, 'valid-logloss': 0.078188, 'valid-error': 0.040936, 'time_this_iter_s': 0.03008890151977539, 'should_checkpoint': True, 'done': True, 'timesteps_total': None, 'episodes_total': None, 'training_iteration': 100, 'trial_id': 'cc863_00000', 'experiment_id': 'dc3dac01a34043cfb5751907e2bc648e', 'date': '2022-06-22_17-29-14', 'timestamp': 1655918954, 'time_total_s': 12.516392230987549, 'pid': 1493910, 'hostname': 'ip-172-31-43-110', 'node_ip': '172.31.43.110', 'config': {}, 'time_since_restore': 12.516392230987549, 'timesteps_since_restore': 0, 'iterations_since_restore': 100, 'warmup_time': 0.004768848419189453, 'experiment_tag': '0'}\n"
]
}
],
"source": [
"result = train_xgboost(num_workers=2, use_gpu=False)"
]
},
{
"cell_type": "markdown",
"id": "7055ad1b",
"metadata": {},
"source": [
"And perform inference on the obtained model:"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "283b1dba",
"metadata": {
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"2022-06-22 17:29:16,463\tWARNING read_api.py:260 -- The number of blocks in this dataset (1) limits its parallelism to 1 concurrent tasks. This is much less than the number of available CPU slots in the cluster. Use `.repartition(n)` to increase the number of dataset blocks.\n",
"Map_Batches: 100%|██████████| 1/1 [00:00<00:00, 46.14it/s]\n",
"Map_Batches: 0%| | 0/1 [00:00<?, ?it/s]\u001b[2m\u001b[36m(pid=1494373)\u001b[0m /home/ubuntu/ray/venv/lib/python3.8/site-packages/xgboost/compat.py:31: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"\u001b[2m\u001b[36m(pid=1494373)\u001b[0m from pandas import MultiIndex, Int64Index\n",
"\u001b[2m\u001b[36m(pid=1494373)\u001b[0m FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"\u001b[2m\u001b[36m(pid=1494373)\u001b[0m FutureWarning: pandas.Float64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"\u001b[2m\u001b[36m(pid=1494373)\u001b[0m FutureWarning: pandas.UInt64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"Map Progress (1 actors 1 pending): 100%|██████████| 1/1 [00:01<00:00, 1.90s/it]\n",
"\u001b[2m\u001b[36m(BlockWorker pid=1494373)\u001b[0m FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"Map_Batches: 100%|██████████| 1/1 [00:00<00:00, 75.10it/s]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"PREDICTED LABELS\n",
"{'predictions': 1}\n",
"{'predictions': 1}\n",
"{'predictions': 0}\n",
"{'predictions': 1}\n",
"{'predictions': 1}\n",
"{'predictions': 1}\n",
"{'predictions': 1}\n",
"{'predictions': 1}\n",
"{'predictions': 0}\n",
"{'predictions': 1}\n",
"{'predictions': 0}\n",
"{'predictions': 1}\n",
"{'predictions': 1}\n",
"{'predictions': 1}\n",
"{'predictions': 1}\n",
"{'predictions': 0}\n",
"{'predictions': 0}\n",
"{'predictions': 1}\n",
"{'predictions': 1}\n",
"{'predictions': 0}\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Map_Batches: 0%| | 0/1 [00:00<?, ?it/s]\u001b[2m\u001b[36m(pid=1494403)\u001b[0m /home/ubuntu/ray/venv/lib/python3.8/site-packages/xgboost/compat.py:31: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"\u001b[2m\u001b[36m(pid=1494403)\u001b[0m from pandas import MultiIndex, Int64Index\n",
"\u001b[2m\u001b[36m(pid=1494413)\u001b[0m /home/ubuntu/ray/venv/lib/python3.8/site-packages/xgboost/compat.py:31: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"\u001b[2m\u001b[36m(pid=1494413)\u001b[0m from pandas import MultiIndex, Int64Index\n",
"\u001b[2m\u001b[36m(pid=1494403)\u001b[0m FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"\u001b[2m\u001b[36m(pid=1494403)\u001b[0m FutureWarning: pandas.Float64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"\u001b[2m\u001b[36m(pid=1494403)\u001b[0m FutureWarning: pandas.UInt64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"\u001b[2m\u001b[36m(pid=1494413)\u001b[0m FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"\u001b[2m\u001b[36m(pid=1494413)\u001b[0m FutureWarning: pandas.Float64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"\u001b[2m\u001b[36m(pid=1494413)\u001b[0m FutureWarning: pandas.UInt64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"Map Progress (1 actors 1 pending): 100%|██████████| 1/1 [00:01<00:00, 1.88s/it]"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"SHAP VALUES\n",
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]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\u001b[2m\u001b[36m(BlockWorker pid=1494413)\u001b[0m FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"\u001b[2m\u001b[36m(pid=1494469)\u001b[0m /home/ubuntu/ray/venv/lib/python3.8/site-packages/xgboost/compat.py:31: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"\u001b[2m\u001b[36m(pid=1494469)\u001b[0m from pandas import MultiIndex, Int64Index\n",
"\u001b[2m\u001b[36m(pid=1494469)\u001b[0m FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"\u001b[2m\u001b[36m(pid=1494469)\u001b[0m FutureWarning: pandas.Float64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
"\u001b[2m\u001b[36m(pid=1494469)\u001b[0m FutureWarning: pandas.UInt64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n"
]
}
],
"source": [
"predict_xgboost(result)"
]
}
],
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