{
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"execution_count": 1,
"id": "0bbb5e31-7578-40b5-b687-80b81064a550",
"metadata": {},
"outputs": [],
"source": [
"import sys\n",
"sys.path.append(\"../src\")"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "b833f6d0-1c26-451a-b951-8dcdfba882c1",
"metadata": {},
"outputs": [],
"source": [
"SPLIT_NUM = 10"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "bfdf015a-d937-4805-9f65-a8fc74df7b46",
"metadata": {},
"outputs": [],
"source": [
"import random\n",
"import os.path as osp\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "6d676ad4-8863-4d4e-88dd-8966dbfe6b41",
"metadata": {},
"outputs": [],
"source": [
"src = pd.read_csv(\"../input/train.csv\", header=None)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "5b6595d5-05e0-4a2e-b932-a2b61f97da05",
"metadata": {},
"outputs": [],
"source": [
"total_data_num = src.shape[0]"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "24a9b217-fa3d-42f9-b2d9-c344889d22f4",
"metadata": {},
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"execution_count": 6,
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{
"cell_type": "code",
"execution_count": 7,
"id": "2c255a0c-0649-48af-970e-919045c5bf18",
"metadata": {},
"outputs": [],
"source": [
"splited_data_num = 32373 // SPLIT_NUM"
]
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{
"cell_type": "code",
"execution_count": 11,
"id": "46cb1fd3-5498-4c98-bbd7-d4c0e3f30bb2",
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{
"cell_type": "code",
"execution_count": 59,
"id": "537dae35-c4a4-49f6-ab4d-69044d9999ed",
"metadata": {},
"outputs": [],
"source": [
"corrects = src[src[3] == True]"
]
},
{
"cell_type": "code",
"execution_count": 61,
"id": "56969660-1a2b-4ae8-9a13-3c8e75411e16",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"<ipython-input-61-5cac1ff16056>:1: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" corrects[\"split\"] = 999\n"
]
}
],
"source": [
"corrects[\"split\"] = 999"
]
},
{
"cell_type": "code",
"execution_count": 63,
"id": "fbb77cb4-0c87-4892-9d06-09678bd7ac6f",
"metadata": {},
"outputs": [],
"source": [
"corrects.to_csv(\"../input/bagging/corrects.csv\", header=None, index=False)"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "389b6072-5e35-474b-85e0-475287ba633f",
"metadata": {},
"outputs": [],
"source": [
"target = src[src[3] == False]"
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "0dca8960-7590-4e30-867a-c3504511e2e6",
"metadata": {},
"outputs": [],
"source": [
"seq_col = []\n",
"for _, row in target.iterrows():\n",
" sample = row[0]\n",
" seq_name = osp.basename(osp.dirname(sample))\n",
" seq_col.append(int(seq_name[-1]))"
]
},
{
"cell_type": "code",
"execution_count": 36,
"id": "d2e221ab-587c-4bab-8595-0e3b126f010a",
"metadata": {},
"outputs": [],
"source": [
"tmp_target = target[target[\"seq\"] == 0]"
]
},
{
"cell_type": "code",
"execution_count": 35,
"id": "d4541d6a-6a90-41e3-b5d9-529efab3b569",
"metadata": {},
"outputs": [],
"source": [
"import itertools"
]
},
{
"cell_type": "code",
"execution_count": 40,
"id": "cf940f00-6106-4614-8ca2-6af12d216b61",
"metadata": {},
"outputs": [],
"source": [
"tmp_split_num = []\n",
"for i in itertools.cycle(range(10)):\n",
" tmp_split_num.append(i)\n",
" if len(tmp_split_num) == tmp_target.shape[0]:\n",
" break\n",
"random.shuffle(tmp_split_num)"
]
},
{
"cell_type": "code",
"execution_count": 44,
"id": "a42ce653-fb5a-4fe1-be52-66e7dd35d15c",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"<ipython-input-44-5da5823ccadb>:10: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" tmp_target[\"split\"] = tmp_split_num\n",
"<ipython-input-44-5da5823ccadb>:10: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" tmp_target[\"split\"] = tmp_split_num\n",
"<ipython-input-44-5da5823ccadb>:10: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" tmp_target[\"split\"] = tmp_split_num\n",
"<ipython-input-44-5da5823ccadb>:10: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" tmp_target[\"split\"] = tmp_split_num\n",
"<ipython-input-44-5da5823ccadb>:10: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" tmp_target[\"split\"] = tmp_split_num\n",
"<ipython-input-44-5da5823ccadb>:10: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" tmp_target[\"split\"] = tmp_split_num\n",
"<ipython-input-44-5da5823ccadb>:10: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" tmp_target[\"split\"] = tmp_split_num\n",
"<ipython-input-44-5da5823ccadb>:10: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" tmp_target[\"split\"] = tmp_split_num\n",
"<ipython-input-44-5da5823ccadb>:10: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" tmp_target[\"split\"] = tmp_split_num\n"
]
}
],
"source": [
"out_df = None\n",
"for seq_num in range(9):\n",
" tmp_target = target[target[\"seq\"] == seq_num]\n",
" tmp_split_num = []\n",
" for split_num in itertools.cycle(range(10)):\n",
" tmp_split_num.append(split_num)\n",
" if len(tmp_split_num) == tmp_target.shape[0]:\n",
" break\n",
" random.shuffle(tmp_split_num)\n",
" tmp_target[\"split\"] = tmp_split_num\n",
" \n",
" if seq_num == 0:\n",
" out_df = tmp_target\n",
" else:\n",
" out_df = pd.concat([out_df, tmp_target], axis=0)"
]
},
{
"cell_type": "code",
"execution_count": 51,
"id": "8906a080-d7b8-48a8-b247-57fe9ebedeb7",
"metadata": {},
"outputs": [],
"source": [
"tmp = out_df[out_df[\"seq\"] == 1]"
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"cell_type": "code",
"execution_count": 53,
"id": "60ea9f62-e3cf-4545-aa7a-d187aefbde6d",
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},
"execution_count": 57,
"metadata": {},
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}
],
"source": [
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]
},
{
"cell_type": "code",
"execution_count": 64,
"id": "dc50ec1e-40f6-4251-b6f6-654614168942",
"metadata": {},
"outputs": [],
"source": [
"out_df.drop(\"seq\", axis=1).to_csv(\"../input/bagging/incorrects.csv\", header=None, index=False)"
]
<<<<<<< HEAD
},
{
"cell_type": "code",
"execution_count": null,
"id": "0fcff95b-80b3-4bb9-abc6-850e6e614962",
"metadata": {},
"outputs": [],
"source": []
=======
>>>>>>> with_ssh
}
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