Fake content detection Kit

I have created this solution as part of the 24 Hour AI Challenge. I have used the base kandi kit for fake news detection and trained the data set. The trained model will help us to validate news content. This news content can be from any domain such as Technology, Medicine and other related content. I have used ML algorithm such as Logistic regression and Naïve Bayes model: Logistic Regression model: Here I have tuned the following parameter: Cs = 15 Each of the values in Cs describes the inverse of regularization strength. cv = 10 The default cross-validation generator used is Stratified K-Folds. max_iter = 300 Maximum number of iterations of the optimization algorithm. multi_class = 'ovr' If the option chosen is ‘ovr’, then a binary problem is fit for each label. Navie Bayes model: Here I have tuned the following parameter: alpha = 0.1 I have also added a demo video in drive at https://drive.google.com/drive/folders/1i6S8UMY8TksAFeSNLJjB2V6kcWRofiBX?usp=sharing