A text classifier for wine reviews crawled from http://winemag.com.
1: Bernoulli Naive Bayes 2: Multinomial Naive Bayes
1: Cross Validation 2: Percentage Split
git clone https://github.com/nirbhayph/Winifier.git
cd Winifier
pip3 install -r requirements.txt
Now that the requirements are satisfied you can use the following options to run the program:
process (whether "train"/"test")
filePath for training (path to dataset, "txt file delimited with ~")
modelFilePath for testing with custom dataset (path to dataset, "txt file delimited with ~")
algorithm (whether "bernoulli"/"multinomial")
type (whether "percentage_split"/"cross_validation")
trainPercentage (if "percentage_split" selected)
numberOfFolds (if "cross_validation" selected)
datasetLimit (number of rows to select from dataset)
<python3 Winifier.py "train" "filePath" datasetLimit "algorithm" "type" "trainPercentage/numberOfFolds">
python3 Winifier.py "train" "__data__/trainingV2.txt" 11110 "bernoulli" "percentage_split" 90
python3 Winifier.py "train" "__data__/trainingV2.txt" 11110 "multinomial" "percentage_split" 90
python3 Winifier.py "train" "__data__/trainingV2.txt" 11110 "bernoulli" "cross_validation" 10
python3 Winifier.py "train" "__data__/trainingV2.txt" 11110 "multinomial" "cross_validation" 10
This is under development, currently we have the option only to train and evaluate at run time! We plan to deliver this option through the next checkpoint
<python3 Winifier.py "test" "filePath" datasetLimit "modelFilePath">
python3 Winifier.py "test" "__data__/trainingV2.txt" 1110 "__model__/generated/multinomial__percentage_split__90.json"
Link to repository: https://github.com/nirbhayph/Winifier.git You can visit this link to see updated ReadMe file if you wish to.
@Authors (Team #5)
Khavya Seshadri Dhiren Chandnani Nirbhay Pherwani