Question
The dataset can be download from here:https://github.com/unt-iialab/info5731_spring2021/blob/main/class_exercises/exercise09_datacollection.zip. The dataset contains two files train data and test data for sentiment analysis in IMDB review, it has
The dataset can be download from here:https://github.com/unt-iialab/info5731_spring2021/blob/main/class_exercises/exercise09_datacollection.zip. The dataset contains two files train data and test data for sentiment analysis in IMDB review, it has two categories: 1 represents positive and 0 represents negative. You need to split the training data into training and validate data (80% for training and 20% for validation,https://towardsdatascience.com/train-test-split-and-cross-validation-in-python-80b61beca4b6) and perform 10 fold cross validation while training the classifier. The final trained model was final evaluated on the test data.
Algorithms:
(1) MultinominalNB
(2) SVM
(3) KNN
(4) Decision tree
(5) Random Forest
(6) XGBoost
Evaluation measurement:
(1) Accuracy
(2) Recall
(3) Precison
(4) F-1 score
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