user knn

import time

from caserec.recommenders.rating_prediction import userknn as userknn_prediction
from caserec.recommenders.item_recommendation import userknn as userknn_recommendation
from caserec.evaluation.item_recommendation import ItemRecommendationEvaluation
from caserec.evaluation.rating_prediction import RatingPredictionEvaluation
from caserec.utils.split_database import SplitDatabase

if __name__ == '__main__':
    print("Iniciando Recommender")

    n_splits = 5
    time_to_split_database = time.time()
    SplitDatabase(
        input_file="files/1000_itens.txt",
        dir_folds="files",
        n_splits=n_splits,
        sep_read='\t',
        sep_write='\t'
    ).k_fold_cross_validation()

    print("Tempo decorrido para dividir o banco de dados: " + str(time_to_split_database))
    print("Iniciando UserKNN")
    time_to_compute_UserKNN = time.time()
    for fold in range(n_splits - 1):

        print("Iniciando fold: " + str(n_splits))

        print("User Knn recommendation.")
        userknn_recommendation.UserKNN(
            train_file="filesfolds/" + str(fold) + "/train.dat",
            test_file="filesfolds/" + str(fold) + "/test.dat",
            output_file="files/output_recommendation.txt",
            sep='\t',
            output_sep='\t',
            as_similar_first=True).compute()

        print("User Knn prediction.")
        userknn_prediction.UserKNN(
            train_file="filesfolds/"+str(fold)+"/train.dat",
            test_file="filesfolds/"+str(fold)+"/test.dat",
            output_file="files/output_prediction.txt",
            sep='\t',
            output_sep='\t',
            as_similar_first=True).compute()

        print("User Knn recommendation evaluation.")
        ItemRecommendationEvaluation().evaluate_with_files(
            prediction_file="files/output_recommendation.txt",
            test_file="filesfolds/"+str(fold)+"/test.dat")

        print("User Knn prediction evaluation.")
        RatingPredictionEvaluation().evaluate_with_files(
            prediction_file="files/output_prediction.txt",
            test_file="filesfolds/" + str(fold) + "/test.dat")

    print("Tempo decorrido para computar o UserKnn: " + str(time_to_compute_UserKNN))