File size: 2,254 Bytes
e8e72fb | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 | from sklearn.feature_extraction.text import TfidfVectorizer, CountVectorizer
from sklearn.naive_bayes import MultinomialNB
from sklearn.pipeline import Pipeline
from sklearn.metrics import classification_report
from sklearn.metrics import confusion_matrix
from sklearn.linear_model import LogisticRegression
import sys
import os
parent_root = os.path.abspath(os.path.join(os.path.dirname(os.path.abspath(__file__)), os.pardir, os.pardir))
sys.path.append(parent_root)
from src.dataset import *
from src.config.configs import Params
param = Params()
## Naives Bayes, Logistic Regression
class BaseLine(object):
def __init__(self, vectorizer, model):
self.vectorizer = vectorizer
self.model = model
def train(self, X_train, y_train, X_val, y_val, X_test, y_test):
model= Pipeline([
("vectorizer", self.vectorizer),
("model", self.model)
])
print("Vectorizer: ", self.vectorizer)
print("Model: ", self.model)
model.fit(X_train, y_train)
val_score = model.score(X_val, y_val)
test_score = model.score(X_test, y_test)
print("Model accuracy on val set", model.score(X_val, y_val))
print("Model accuracy on test set", model.score(X_test, y_test))
return val_score, test_score
if __name__ == "__main__":
print("---------------Baseline ML model------------------------")
params = Params()
# Define dataset
dataset = Dataset(train_txt=params.TRAIN_DIR, val_txt=params.VAL_DIR, test_txt=params.TEST_DIR, num_inputs=1)
# Define train/val/test
train_sentences = dataset.train_sentences
val_sentences = dataset.val_sentences
test_sentences = dataset.test_sentences
y_train = dataset.y_train
y_val = dataset.y_val
y_test = dataset.y_test
val_score, test_score =BaseLine(vectorizer=TfidfVectorizer(),
model=LogisticRegression()).train(
X_train=train_sentences, y_train=y_train,
X_val=val_sentences, y_val=y_val,
X_test=test_sentences, y_test=y_test)
print("Baseline Val score: ", val_score)
print("Baseline Test score: ", test_score) |