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almohanad.hafez
NLP-Project
Commits
b355fbd8
Commit
b355fbd8
authored
Nov 22, 2024
by
Almouhannad Hafez
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4a19d3ea
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11 changed files
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1535 additions
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1418 deletions
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-1418
1.1.Dataset_Overview.ipynb
1.1.Dataset_Overview.ipynb
+0
-1354
1.1.Dataset_Overview.ipynb
1/1.1.Dataset_Overview.ipynb
+1367
-0
1.2.Data_Preprocessing.ipynb
1/1.2.Data_Preprocessing.ipynb
+32
-19
2.Stemmer.ipynb
2/2.Stemmer.ipynb
+32
-19
3.1.Lemmatizer.ipynb
3/3.1.Lemmatizer.ipynb
+16
-3
3.2.POS_Tagging_Filter.ipynb
3/3.2.POS_Tagging_Filter.ipynb
+16
-3
3.3.N-Grams.ipynb
3/3.3.N-Grams.ipynb
+16
-3
4.Data_augmentation.ipynb
4/4.Data_augmentation.ipynb
+16
-3
5.0.Process_texts_stanza.ipynb
5/5.0.Process_texts_stanza.ipynb
+16
-3
5.1.Dep_parsing_classifier.ipynb
5/5.1.Dep_parsing_classifier.ipynb
+16
-3
constants.py
constants.py
+8
-8
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1.1.Dataset_Overview.ipynb
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.2.Data_Preprocessing.ipynb
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b355fbd8
...
@@ -17,9 +17,7 @@
...
@@ -17,9 +17,7 @@
"from sklearn.utils import shuffle\n",
"from sklearn.utils import shuffle\n",
"from sklearn.model_selection import train_test_split\n",
"from sklearn.model_selection import train_test_split\n",
"\n",
"\n",
"import contractions\n",
"import contractions"
"\n",
"from constants import CONSTANTS"
]
]
},
},
{
{
...
@@ -27,6 +25,21 @@
...
@@ -27,6 +25,21 @@
"execution_count": 2,
"execution_count": 2,
"metadata": {},
"metadata": {},
"outputs": [],
"outputs": [],
"source": [
"import sys\n",
"import os\n",
"parent_dir = os.path.abspath('..')\n",
"sys.path.append(parent_dir)\n",
"from constants import CONSTANTS\n",
"%load_ext autoreload\n",
"%autoreload 2"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"source": [
"df = pd.read_csv(CONSTANTS.DATASET_PATH)"
"df = pd.read_csv(CONSTANTS.DATASET_PATH)"
]
]
...
@@ -40,7 +53,7 @@
...
@@ -40,7 +53,7 @@
},
},
{
{
"cell_type": "code",
"cell_type": "code",
"execution_count":
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"execution_count":
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"metadata": {},
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"outputs": [],
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},
},
{
{
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"execution_count":
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"metadata": {},
"metadata": {},
"outputs": [
"outputs": [
{
{
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"4 4 Psoriasis My nails have small dents or pits in them, and..."
"4 4 Psoriasis My nails have small dents or pits in them, and..."
]
]
},
},
"execution_count":
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"execution_count":
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"metadata": {},
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"output_type": "execute_result"
}
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},
},
{
{
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"metadata": {},
"metadata": {},
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"outputs": [
{
{
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"4 My nails have small dents or pits in them, and... Psoriasis"
"4 My nails have small dents or pits in them, and... Psoriasis"
]
]
},
},
"execution_count":
5
,
"execution_count":
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"metadata": {},
"metadata": {},
"output_type": "execute_result"
"output_type": "execute_result"
}
}
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},
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{
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"metadata": {},
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{
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},
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{
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},
},
{
{
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"cell_type": "code",
"execution_count":
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"execution_count":
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"metadata": {},
"metadata": {},
"outputs": [
"outputs": [
{
{
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"4 I've been quite exhausted and ill. My throat h... Common Cold"
"4 I've been quite exhausted and ill. My throat h... Common Cold"
]
]
},
},
"execution_count":
8
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"execution_count":
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"metadata": {},
"metadata": {},
"output_type": "execute_result"
"output_type": "execute_result"
}
}
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},
},
{
{
"cell_type": "code",
"cell_type": "code",
"execution_count":
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"execution_count":
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"metadata": {},
"metadata": {},
"outputs": [
"outputs": [
{
{
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},
},
{
{
"cell_type": "code",
"cell_type": "code",
"execution_count": 1
0
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"execution_count": 1
1
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"metadata": {},
"metadata": {},
"outputs": [
"outputs": [
{
{
...
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"4 i've been quite exhausted and ill. my throat h... common cold"
"4 i've been quite exhausted and ill. my throat h... common cold"
]
]
},
},
"execution_count": 1
0
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"execution_count": 1
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"metadata": {},
"metadata": {},
"output_type": "execute_result"
"output_type": "execute_result"
}
}
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},
},
{
{
"cell_type": "code",
"cell_type": "code",
"execution_count": 1
1
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"execution_count": 1
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"metadata": {},
"metadata": {},
"outputs": [
"outputs": [
{
{
...
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...
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"4 i have been quite exhausted and ill. my throat... common cold"
"4 i have been quite exhausted and ill. my throat... common cold"
]
]
},
},
"execution_count": 1
1
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"execution_count": 1
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"metadata": {},
"metadata": {},
"output_type": "execute_result"
"output_type": "execute_result"
}
}
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},
},
{
{
"cell_type": "code",
"cell_type": "code",
"execution_count": 1
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"execution_count": 1
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"metadata": {},
"metadata": {},
"outputs": [
"outputs": [
{
{
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},
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{
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"cell_type": "code",
"execution_count": 1
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"outputs": [],
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2.Stemmer.ipynb
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/2
.Stemmer.ipynb
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b355fbd8
...
@@ -28,9 +28,22 @@
...
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"\n",
"\n",
"from tabulate import tabulate\n",
"from tabulate import tabulate\n",
"\n",
"\n",
"import pandas as pd\n",
"import pandas as pd"
"\n",
]
"from constants import CONSTANTS"
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import sys\n",
"import os\n",
"parent_dir = os.path.abspath('..')\n",
"sys.path.append(parent_dir)\n",
"from constants import CONSTANTS\n",
"%load_ext autoreload\n",
"%autoreload 2"
]
]
},
},
{
{
...
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...
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},
},
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"execution_count":
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"execution_count":
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"metadata": {},
"metadata": {},
"outputs": [],
"outputs": [],
"source": [
"source": [
...
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},
},
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"execution_count":
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"outputs": [],
"source": [
"source": [
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},
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"execution_count":
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"outputs": [],
"source": [
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},
},
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"execution_count":
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"outputs": [],
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},
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},
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"execution_count":
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"outputs": [],
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},
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"execution_count":
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"source": [
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},
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"outputs": [
{
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},
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},
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},
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"outputs": [
{
{
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"MultinomialNB(alpha=0.1)"
"MultinomialNB(alpha=0.1)"
]
]
},
},
"execution_count": 1
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"metadata": {},
"output_type": "execute_result"
"output_type": "execute_result"
}
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},
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},
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{
{
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3.1.Lemmatizer.ipynb
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/3
.1.Lemmatizer.ipynb
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b355fbd8
...
@@ -42,9 +42,22 @@
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"\n",
"\n",
"from tabulate import tabulate\n",
"from tabulate import tabulate\n",
"\n",
"\n",
"import pandas as pd\n",
"import pandas as pd"
"\n",
]
"from constants import CONSTANTS"
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import sys\n",
"import os\n",
"parent_dir = os.path.abspath('..')\n",
"sys.path.append(parent_dir)\n",
"from constants import CONSTANTS\n",
"%load_ext autoreload\n",
"%autoreload 2"
]
]
},
},
{
{
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.2.POS_Tagging_Filter.ipynb
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b355fbd8
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"\n",
"\n",
"from tabulate import tabulate\n",
"from tabulate import tabulate\n",
"\n",
"\n",
"import pandas as pd\n",
"import pandas as pd"
"\n",
]
"from constants import CONSTANTS"
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import sys\n",
"import os\n",
"parent_dir = os.path.abspath('..')\n",
"sys.path.append(parent_dir)\n",
"from constants import CONSTANTS\n",
"%load_ext autoreload\n",
"%autoreload 2"
]
]
},
},
{
{
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/3
.3.N-Grams.ipynb
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b355fbd8
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"\n",
"\n",
"from tabulate import tabulate\n",
"from tabulate import tabulate\n",
"\n",
"\n",
"import pandas as pd\n",
"import pandas as pd"
"\n",
]
"from constants import CONSTANTS\n"
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import sys\n",
"import os\n",
"parent_dir = os.path.abspath('..')\n",
"sys.path.append(parent_dir)\n",
"from constants import CONSTANTS\n",
"%load_ext autoreload\n",
"%autoreload 2"
]
]
},
},
{
{
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/4
.Data_augmentation.ipynb
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"\n",
"\n",
"from ollama import Client\n",
"from ollama import Client\n",
"\n",
"\n",
"import re\n",
"import re"
"\n",
]
"from constants import CONSTANTS"
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import sys\n",
"import os\n",
"parent_dir = os.path.abspath('..')\n",
"sys.path.append(parent_dir)\n",
"from constants import CONSTANTS\n",
"%load_ext autoreload\n",
"%autoreload 2"
]
]
},
},
{
{
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/5
.0.Process_texts_stanza.ipynb
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b355fbd8
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"\n",
"\n",
"import stanza\n",
"import stanza\n",
"\n",
"\n",
"import pickle # Module to store python objects\n",
"import pickle # Module to store python objects"
"\n",
]
"from constants import CONSTANTS"
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import sys\n",
"import os\n",
"parent_dir = os.path.abspath('..')\n",
"sys.path.append(parent_dir)\n",
"from constants import CONSTANTS\n",
"%load_ext autoreload\n",
"%autoreload 2"
]
]
},
},
{
{
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/5
.1.Dep_parsing_classifier.ipynb
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b355fbd8
...
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...
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"from sklearn.model_selection import train_test_split\n",
"from sklearn.model_selection import train_test_split\n",
"from sklearn.metrics import accuracy_score, classification_report\n",
"from sklearn.metrics import accuracy_score, classification_report\n",
"\n",
"\n",
"from tabulate import tabulate\n",
"from tabulate import tabulate"
"\n",
]
"from constants import CONSTANTS"
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import sys\n",
"import os\n",
"parent_dir = os.path.abspath('..')\n",
"sys.path.append(parent_dir)\n",
"from constants import CONSTANTS\n",
"%load_ext autoreload\n",
"%autoreload 2"
]
]
},
},
{
{
...
...
constants.py
View file @
b355fbd8
class
CONSTANTS
:
class
CONSTANTS
:
DATASET_PATH
=
'data/Symptom2Disease.csv'
DATASET_PATH
=
'
../
data/Symptom2Disease.csv'
TRAIN_SET_PATH
=
'data/Preprocessed_Symptom2Disease_Train.csv'
TRAIN_SET_PATH
=
'
../
data/Preprocessed_Symptom2Disease_Train.csv'
TEST_SET_PATH
=
'data/Preprocessed_Symptom2Disease_Test.csv'
TEST_SET_PATH
=
'
../
data/Preprocessed_Symptom2Disease_Test.csv'
AUGMENTED_DATASET_PATH
=
'data/augmented_Symptom2Disease.csv'
AUGMENTED_DATASET_PATH
=
'
../
data/augmented_Symptom2Disease.csv'
AUGMENTED_TRAIN_SET_PATH
=
'data/augmented_Preprocessed_Symptom2Disease_Train.csv'
AUGMENTED_TRAIN_SET_PATH
=
'
../
data/augmented_Preprocessed_Symptom2Disease_Train.csv'
AUGMENTED_TEST_SET_PATH
=
'data/augmented_Preprocessed_Symptom2Disease_Test.csv'
AUGMENTED_TEST_SET_PATH
=
'
../
data/augmented_Preprocessed_Symptom2Disease_Test.csv'
LEMMATIZED_TEXTS_OBJECT_PATH
=
'stanza/lemmatized_texts.pkl'
LEMMATIZED_TEXTS_OBJECT_PATH
=
'../stanza/lemmatized_texts.pkl'
DEP_PARSED_TEXTS_OBJECT_PATH
=
'stanza/dep_parsed_texts.pkl'
DEP_PARSED_TEXTS_OBJECT_PATH
=
'../stanza/dep_parsed_texts.pkl'
\ No newline at end of file
\ No newline at end of file
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