Update oneclass.py

oneclass.py

@@ -2,7 +2,7 @@ import pandas as pd
 from sklearn.feature_extraction.text import TfidfVectorizer
 from sklearn.svm import OneClassSVM
 
-def select_top_n_papers(n, positive_csv_file, unlabelled_csv_file):
+def select_top_n_papers(n, positive_csv_file, unlabelled_csv_file,nu):
     # Load the positive labelled and unlabelled data
     positive_labelled_info = pd.read_csv(positive_csv_file)
     unlabelled_labelled = pd.read_csv(unlabelled_csv_file)
@@ -16,7 +16,7 @@ def select_top_n_papers(n, positive_csv_file, unlabelled_csv_file):
     X_pos = vectorizer.fit_transform(positive_labelled_info['text'])
 
     # Train a one-class SVM model
-    clf = OneClassSVM(kernel='rbf', nu=0.7)  # Adjust parameters as needed
+    clf = OneClassSVM(kernel='rbf', nu=nu)  # Adjust parameters as needed
     clf.fit(X_pos)
 
     # Transform unlabelled data using the same vectorizer