Add files

best_forest.joblib

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+version https://git-lfs.github.com/spec/v1
+oid sha256:1fe94c3c3d4ef118f6fb2e423562cfcf91a6d44b4dab1ebf523a8b0d78ac7aaa
+size 21323097

best_knn.joblib

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+version https://git-lfs.github.com/spec/v1
+oid sha256:1c4bd87ac0d26fe7f9d8e5efa89a98b859c785b379f97f51c643f2c23e856253
+size 10372500

best_lreg.joblib

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+version https://git-lfs.github.com/spec/v1
+oid sha256:629ed82434ff08e7538a34f9d82c989af76af5cf990ef6f340fe306ab39d495b
+size 30399

best_svm.joblib

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+version https://git-lfs.github.com/spec/v1
+oid sha256:8bfd050d13b118192ee11d8f5829cf5298ad37fb111d8de552611d5b4527053e
+size 6305515

main.py

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+import joblib
+import pandas as pd
+import gradio as gr
+
+vec = joblib.load('vectorizer.joblib')
+feature_names = vec.get_feature_names_out()
+
+knn = joblib.load('best_knn.joblib')
+lreg = joblib.load('best_lreg.joblib')
+svm = joblib.load('best_svm.joblib')
+forest = joblib.load('best_forest.joblib')
+
+knn_label = "KNN Classifier"
+lreg_label = "Logistic Regression"
+svm_label = "Support Vector Machine"
+forest_label = "Random Forest"
+
+str_to_model = {
+    knn_label: knn,
+    lreg_label: lreg,
+    svm_label: svm,
+    forest_label: forest
+}
+
+review_input = gr.Textbox(label = 'Review Comment')
+dropdown_input = gr.Dropdown([knn_label, lreg_label, svm_label, forest_label], label='Method')
+
+def multi_inputs(review, model_label):
+  model = str_to_model[model_label]
+  mat = vec.transform([review])
+  bow = pd.DataFrame(mat.toarray(), columns=feature_names)
+
+  a = model.predict(bow)[0]
+  b = model.predict_proba(bow)[0]
+
+  out1 = 'Negative comment' if a == 0 else 'Positive comment'
+  out2 = f'{b[0]*100:.0f}%'
+  out3 = f'{b[1]*100:.0f}%'
+
+  return out1, out2, out3

vectorizer.joblib

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+version https://git-lfs.github.com/spec/v1
+oid sha256:d0409295b1d9c8360c83b1b778455dbd024edabac40718fc7c2ff9c5616464dc
+size 20862