def GetNearRest(uid): con= databaseCon.Database() return json.dumps(con.NearRestaurants(uid),indent=2)
def GetNameRest(uid): con= databaseCon.Database() return json.dumps(con.getRestoName(),indent=2)
def RateRestaurant(Restaurantid,value,uid): con= databaseCon.Database() return con.RateRestaurant(Restaurantid,value,uid)
def GetUser(uid): con= databaseCon.Database() return json.dumps(con.getUser(uid),indent=2)
def createUser(uid): con= databaseCon.Database() return con.CreatetUser(uid)
def getUser(uid): print("Came here") con = databaseCon.Database() return json.dumps(con.getUser(uid),indent=2)
from surprise import SVD import pandas as pd from surprise import Dataset from surprise import Reader from collections import defaultdict from surprise.model_selection import cross_validate import databaseCon con = databaseCon.Database() loadedData = con.selectAll() userGroupId = loadedData[0] ingredientId = loadedData[1] ratings = loadedData[2] def do_Predict(): ratings_dict = { 'userID': userGroupId, 'itemID': ingredientId, 'rating': ratings } df = pd.DataFrame(ratings_dict) reader = Reader(rating_scale=(1, 4)) data = Dataset.load_from_df(df[['userID', 'itemID', 'rating']], reader) trainset = data.build_full_trainset() algo = SVD() algo.fit(trainset) testset = trainset.build_anti_testset() predictions = algo.test(testset) cross_validate(algo, data, measures=['RMSE', 'MAE'], cv=5, verbose=True)
def rateItem(itemName, ratedValue, uid): con = databaseCon.Database() return con.rateItem(itemName, ratedValue, uid)