predict the vids-agg(total) number of vids-ent(orders) where the vids-flt(preferred_type_of_food) vids-flo(is) chinese for the next vids-prw(week)|NONE|Preference(P1)|is equal to|total|Order|week
predict the vids-agg(total) number of vids-ent(orders) will be placed in the grubhub website in atlanta for the next vids-prw(week) where the customer usually vids-flt(prefer_chinease_food)|NONE|Preference(P1)|is equal to|total|Order|week
I want to know the vids-agg(total) count of vids-ent(order) in delivary medium where the vids-flt(order_medium) vids-flo(is) online within vids-prw(tomorrow)|NONE|Medium (P1)|is equal to|total|Order|tomorrow
I want to know the vids-agg(total) count of vids-ent(order) in resturants located at downtown of Atlanta where the customers would like to vids-flt(order_food_online) within the day end of vids-prw(tomorrow)|NONE|Medium (P1)|is equal to|total|Order|tomorrow
predict the vids-agg(total) number of vids-ent(orders) is case where the vids-flt(marital_status_of_customer) vids-flo(is) married and vids-flt(income_of_customer) vids-flo(is_greater_than) vids-num(two_thousand) within next vids-num(two) vids-prw(weeks)|NONE|Marital Status, monthly income|is equal to, is_greater_than|total|Order|weeks
predict the vids-agg(total) number of vids-ent(orders) placed by vids-flt(married_customers) in the weekends or after the office hours and those vids-flt(customers_income) vids-flo(is_more_than) vids-num(two_thousand) monthly within next vids-num(two) vids-prw(weeks)|NONE|Marital Status, monthly income|is equal to, is_more_than|total|Order|weeks
predict the vids-agg(average) number of reduction of vids-ent(order) in delivary medium because of vids-flt(bad_hygiene_quality_of_food) and so there is vids-flt(concern_in_health)|NONE|Poor Hygiene, Health Concern|is equal to|average|Order|NONE
predict the vids-agg(average) vids-ent(order) will be reduced in those resturants of which vids-flt(food_hygiene) is getting worse over the time and so there is vids-flt(concern_in_health) among the customers|NONE|Poor Hygiene, Health Concern|is equal to|average|Order|NONE
I would like to predict the vids-agg(total) vids-atr(mistaken_orders) when the customer vids-flt(stays_in_a_busy_location) for the next vids-prw(week)|Order_placed_by_mistake|Residence in busy location|is equal to|total|Order|week
I would like to predict the vids-agg(total) vids-atr(mistaken_orders) by customer through grubhub or uber eats website when the customer vids-flt(stays_in_a_busy_location) like the downtown of Atlanta for the next vids-prw(week)|Order_placed_by_mistake|Residence in busy location|is equal to|total|Order|week
I want to know the vids-agg(maximum) vids-atr(order_placed_by_mistake) where the vids-flt(customers_age) vids-flo(is_less_than) vids-num(21) for the next vids-prw(week)|Order_placed_by_mistake|Age|is_less_than|maximum|Order|week
I want to know the vids-agg(maximum) number of vids-atr(order_will_be_placed_by_mistake) by vids-flt(young_customers) to be precise the age group of vids-flo(less_than) vids-num(21) years old for the next vids-prw(week)|Order_placed_by_mistake|Age|is_less_than|maximum|Order|week
predict the vids-agg(total) reported number of vids-atr(item_gone_missing) where the vids-flt(customer’s_gender) vids-flo(is) female for the next vids-prw(week)|Missing item|Gender|is equal to|total|Order|week
I wnat to know the vids-agg(average) reported number of vids-atr(items_gone_missing) when the order is delivered to a vids-flt(female_customer) and she reported a complaint in the delivary medium for the next vids-prw(week)|Missing item|Gender|is equal to|total|Order|week
predict the vids-agg(total) vids-atr(wrongly_placed_order) where the vids-flt(the_customer) vids-flo(is) job holder for vids-prw(tomorrow)|Order_placed_by_mistake|Occupation|is equal to|total|Order|week
predict the vids-agg(total) vids-atr(wrong_order) placed in grubhub website and later it got cancelled even though it was sent out for delivary where the vids-flt(the_customer) vids-flo(is) job holder for vids-prw(tomorrow)|Order_placed_by_mistake|Occupation|is equal to|total|Order|week
can you tell me the vids-agg(average) vids-atr(accurately_located_order) where the customer vids-flo(is) vids-flt(highly_educated) over the next vids-prw(week)|Google Maps Accuracy|Educational Qualifications|is equal to|average|Order|week
can you tell me the vids-agg(average) order with vids-atr(accurate_location) of the destination on the map by the customer who vids-flo(is) vids-flt(highly_educated) over the next vids-prw(week)|Google Maps Accuracy|Educational Qualifications|is equal to|average|Order|week
predict vids-agg(how_much) vids-atr(high_quality_food) will be ordered where the customers vids-flt(family) has vids-flo(more_than) vids-num(four) members|Good Food quality|Family size|is_more_than|total|NONE|NONE
predict vids-agg(how_much) order will be placed to a resturant who serves vids-atr(high_quality_food) through online food delivary website where the customers vids-flt(family) have vids-flo(more_than) vids-num(four) members|Good Food quality|Family size|is_more_than|total|NONE|NONE
predict the vids-agg(total) vids-ent(order) in delivary medium vids-atr(placed_through) online where vids-flt(customers_age) vids-flo(is_more_than) vids-num(40) over the next vids-prw(week)|Medium (P1)|Age|is_more_than|total|Order|week
predict the vids-agg(total) vids-ent(order) in delivary medium vids-atr(placed_through) online where the vids-flt(age) demographic of the customer vids-flo(is_older_than) vids-num(40) to vids-num(50) years over the next vids-prw(week)|Medium (P1)|Age|is_more_than|total|Order|week
predict the vids-agg(total) vids-ent(order) in delivary medium vids-atr(placed_through) online where vids-flt(family_size_meal) vids-flo(is) preferred over the next vids-prw(week)|Medium (P1)|Meal(P1)|is equal to|total|Order|week
predict the vids-agg(total) vids-flt(family_size_meal) will be vids-ent(ordered) in the delivary medium vids-atr(through_online) over the next vids-prw(week)|Medium (P1)|Meal(P1)|is equal to|total|Order|week
predict the vids-agg(total) vids-ent(order) in delivary medium where vids-flt(Indian_food) vids-flo(is) preferred for the next vids-prw(week)|NONE|Preference(P1)|is equal to|total|Order|week
predict the vids-agg(total) vids-ent(order) will be placed in the uber eats website in the downtown Atlanta area where vids-flt(Indian_food) vids-flo(is) preferred by the customers for the next vids-prw(week)|NONE|Preference(P1)|is equal to|total|Order|week
predict the vids-agg(total) vids-ent(order) in delivary medium where vids-flt(online_order_is_easy) over the next vids-prw(week)|NONE|Ease and convenient|is equal to|total|Order|week
predict the vids-agg(total) vids-ent(order) in delivary medium where the design of the website makes it vids-flt(easy_to_order_online) from different resturants over the next vids-prw(week)|NONE|Ease and convenient|is equal to|total|Order|week
predict the vids-agg(total) vids-ent(order) in delivary medium where the customer vids-flo(has_more_than) vids-num(three) vids-flt(restaurant_options) for the next vids-prw(week)|NONE|More restaurant choices|is_more_than|total|Order|week
predict the vids-agg(total) vids-ent(order) in a delivary medium where it provides customer vids-flo(has_more_than) vids-num(three) vids-flt(restaurant_options) for the same category of food for the next vids-prw(week)|NONE|More restaurant choices|is_more_than|total|Order|week
I want to know the vids-agg(maximum) vids-ent(order) in delivary medium placed where customer can vids-flt(pay_easily) over the next vids-prw(week)|NONE|Easy Payment option|is equal to|maximum|Order|week
I want to know the vids-agg(maximum) vids-ent(order) in delivary medium placed where the vids-flt(payment_ontion) provided to the customer are reliable and vids-flt(very_easy) to use over the next vids-prw(week)|NONE|Easy Payment option|is equal to|maximum|Order|week
predict the vids-agg(total) vids-atr(offers_and_discounts) for the vids-flt(customer) vids-flo(under) vids-num(21) over the next vids-prw(week)|More Offers and Discount|Age|is_less_than|total|NONE|week
predict the vids-agg(total) increase in vids-ent(order) because of the announced vids-atr(offers_and_discounts) campaign by the delivary medium for the demographic of vids-flt(customer) vids-flo(under) vids-num(21) over the next vids-prw(week)|More Offers and Discount|Age|is_less_than|total|NONE|week
predict the vids-agg(total) vids-atr(good_quality_food) vids-ent(ordered) where vids-flt(customers’_age) vids-flo(is_more_than) vids-num(40) over the next vids-prw(week)|Good Food quality|Age|is_more_than|total|Order|week
predict the vids-agg(total) vids-ent(ordered) in the resturants who are popular for vids-atr(food_quality) where vids-flt(customers_age) demographic vids-flo(is_more_than) vids-num(40) over the next vids-prw(week)|Good Food quality|Age|is_more_than|total|Order|week
predict the vids-agg(total) vids-ent(order) in delivary medium delivered with vids-atr(good_tracking_system) where vids-flt(age_of_customer) vids-flo(is_more_than) 30 within next vids-prw(week)|Good Tracking system|Age|vids-flo(is_more_than)|vids-agg(total)|Order|vids-prw(week)
predict the vids-agg(total) vids-ent(order) in delivary medium who provides vids-atr(good_tracking_system) of delivary person in their app where vids-flt(age_demographic) of the app user vids-flo(is_more_than) vids-num(30) within next vids-prw(week)|Good Tracking system|Age|vids-flo(is_more_than)|vids-agg(total)|Order|vids-prw(week)
I want to know the vids-agg(maximum) number of vids-ent(order) in delivary medium will be reduced for vids-atr(self_cooking) where the customers vids-flt(family) vids-flo(is_bigger_than) vids-num(four) within next vids-prw(week)|Self Cooking|Family size|is_more_than|maximum|Order|week
I want to know the vids-agg(maximum) number of vids-ent(order) in delivary medium will be reduced because the customer is shifting towards vids-atr(self_cooking) where the customers vids-flt(family) vids-flo(is_bigger_than) vids-num(four) within next vids-prw(week)|Self Cooking|Family size|is_more_than|maximum|Order|week
predict vids-agg(how_many) vids-ent(order) in delivary medium will be reduced because of vids-atr(health_concern) of food where the customers vids-flt(family_size) vids-flo(is_more_than) vids-num(four) within next vids-prw(week)|Health Concern|Family size|is_more_than|maximum|Order|week
predict vids-agg(how_many) vids-ent(order) in delivary medium will be reduced because of the ongoing trend about vids-atr(healthy_food) consumption and avoiding junk food where the consumer with vids-flt(family_size) vids-flo(is_more_than) vids-num(four) and they might have kids in the family within next vids-prw(week)|Health Concern|Family size|is_more_than|maximum|Order|week
predict on vids-agg(average) how many vids-ent(order) in delivary medium will be cancelled for vids-atr(late_delivary) where the vids-flt(customer’s_age) vids-flo(is_less_than) vids-num(21) for the next vids-prw(week)|Late Delivery|Age|is_less_than|average|Order|week
predict on vids-agg(average) how many vids-ent(order) in delivary medium will be cancelled for vids-atr(late_delivary) time and what will be the tolerance level of the customer where the vids-flt(customer’s_age) demographic vids-flo(is_less_than) vids-num(21) years old for the next vids-prw(week)|Late Delivery|Age|is_less_than|average|Order|week
predict the vids-agg(total) number of vids-ent(order) in delivary medium reduced because of vids-atr(poor_hygiene_quality) of food where the customer vids-flo(is) vids-flt(job_holder) for vids-prw(tomorrow)|Poor Hygiene|Occupation|is equal to|total|Order|week
predict the vids-agg(total) number of vids-ent(order) in delivary medium reduced because most of the added chain resturant in the website does not maintain vids-atr(descent_hygiene_quality) in their store as a result the consumer is concern about the food where the customer vids-flo(is) vids-flt(job_holder) for vids-prw(tomorrow)|Poor Hygiene|Occupation|is equal to|total|Order|week
I want to know vids-agg(how_many) vids-ent(order) in delivary medium will be reduced for vids-atr(bad_experience) where the customer vids-flo(is) vids-flt(job holder) for vids-prw(tomorrow)|Bad past experience|Occupation|is equal to|total|Order|week
I want to know vids-agg(how_many) people will not vids-ent(order) in delivary medium because of the vids-atr(bad_experience) they have faced recently and also have reported the experience with the helpline where the customer vids-flo(is) vids-flt(job holder) for vids-prw(tomorrow)|Bad past experience|Occupation|is equal to|total|Order|week
predict the vids-agg(total) number of vids-ent(order) in delivary medium reduced because of the vids-atr(unavailability) of the food where the customer have vids-flo(is_more_than) vids-num(four) vids-flt(family_members) over next vids-prw(week)|unavailability|Family size|is_more_than|total|Order|week
predict the vids-agg(total) number of vids-ent(order) in delivary medium reduced because in their website medetrenian cuisine resturant are vids-atr(unavailabe) of the food where the customer have vids-flo(is_more_than) vids-num(four) vids-flt(family_members) over next vids-prw(week)|unavailability|Family size|is_more_than|total|Order|week
predict the vids-agg(total) number of vids-ent(order) in delivary medium reduced for being vids-atr(unaffordable) to a customer where the vids-flt(customer’s_age) vids-flo(is_under) vids-num(21) over the next vids-prw(week)|Unaffordable|Age|is_less_than|total|Order|week
predict the vids-agg(total) number of vids-ent(order) in delivary medium will be reducing as the website in claiming more royalty as a result the food ha become vids-atr(unaffordable) to some customer with vids-flt(age) vids-flo(under) vids-num(21) over the next vids-prw(week)|Unaffordable|Age|is_less_than|total|Order|week
predict the vids-agg(total) vids-atr(delivary_assignment_delay) where the customer vids-flt(is_in_busy_location) over the next vids-prw(week)|Delay of delivery person getting assigned|Residence in busy location|is equal to|total|Order|week
predict the vids-agg(average) vids-atr(assignment_delay) of the delivary person through the website which indicates the efficiency of the website design and if it can scale up where the customer vids-flt(is_in_busy_location) over the next vids-prw(week)|Delay of delivery person getting assigned|Residence in busy location|is equal to|total|Order|week
predict the vids-agg(total) vids-atr(food_pickup_delay) where the customer vids-flo(is) vids-flt(living_in_a_busy_area) for the next vids-prw(week)|Delay of delivery person picking up food|Residence in busy location|is equal to|total|Order|week
predict the vids-agg(overall) vids-atr(food_pickup_delay) by a delivary person where the customer vids-flo(is) vids-flt(ordering_from_a_busy_area) like the downtown of Atlanta over the next vids-prw(week)|Delay of delivery person picking up food|Residence in busy location|is equal to|total|Order|week
predict the vids-agg(total) vids-atr(delivary_person_assignment_delay) where the customers location vids-flo(is) not vids-flt(accurately_located_on_google_map)  for the next vids-prw(week)|Delay of delivery person getting assigned|Google Maps Accuracy|is equal to|total|Order|week
predict the vids-agg(total) vids-atr(delivary_person_assignment_delay) in the Zomato website when the customers location on map vids-flo(is) not vids-flt(accurately_located) as a result the website can not make decision quickly for the next vids-prw(week)|Delay of delivery person getting assigned|Google Maps Accuracy|is equal to|total|Order|week
predict the vids-agg(total) vids-atr(food_pickup_delay) where the vids-flt(ability_of_delivery_person) vids-flo(is) not good over the next vids-prw(week)|Delay of delivery person picking up food|Delivery person ability|vids-flo(is) equal to|vids-agg(total)|Order|vids-prw(week)
predict the vids-agg(total) vids-atr(delay_to_pickup_food) by the delivary person indicating the website is not assigning order to correct location but more importantly how the vids-flt(ability_of_delivery_person) vids-flo(is) affecting this metric over the next vids-prw(week)|Delay of delivery person picking up food|Delivery person ability|vids-flo(is) equal to|vids-agg(total)|Order|vids-prw(week)
I want to know the vids-agg(total) vids-ent(orders) with vids-atr(good_review) where the vids-flt(road_condition) of customers residence vids-flo(is) good over the next vids-prw(week)|Reviews|Good Road Condition|is equal to|total|Order|week
I want to know the vids-agg(how_many) vids-ent(orders) have a vids-atr(good_review) to them where the vids-flt(road_condition) of customers residencial area vids-flo(is) good and does not have much traffic as a result the customer is getting food very quickly over the next vids-prw(week)|Reviews|Good Road Condition|is equal to|total|Order|week
predict the vids-agg(total)  vids-atr(high_food_quantity) vids-ent(orders) where the customer’s vids-flt(family_contains) vids-flo(more_than) vids-num(four) members over the next vids-prw(week)|Good Quantity|Family size|is_more_than|total|Order|week
predict the vids-agg(total) amount of vids-atr(big) vids-ent(orders) and we want to know if the customer’s vids-flt(family_contains) vids-flo(more_than) vids-num(four) members  do they order more food over the next vids-prw(week)|Good Quantity|Family size|is_more_than|total|Order|week
predict the vids-agg(latest) vids-atr(time_of_order) where customer’s recidence vids-flt(road_condition) vids-flo(is) good for vids-prw(tomorrow)|Order Time|Good Road Condition|is equal to|maximum|Order|tomorrow
predict the vids-agg(latest) vids-atr(time_of_order) at the night in the downtown are of Atlanta where the vids-flt(road_condition) of customer’s recidence vids-flo(is) good for vids-prw(tomorrow)|Order Time|Good Road Condition|is equal to|maximum|Order|tomorrow
predict the vids-agg(average) vids-atr(number_of_calls) where the vids-flt(delivery_person) vids-flo(is) new over the next vids-prw(week)|Number of calls|Delivery person ability|is equal to|average|Order|week
predict the vids-agg(average) vids-atr(number_of_calls) made by delivary person to the customer as he could not find the customer's house where the vids-flt(delivery_person) vids-flo(is) new over the next vids-prw(week)|Number of calls|Delivery person ability|is equal to|average|Order|week
predict the vids-agg(average) vids-atr(amount_of_calls) by delivery person where the customers vids-flt(location) vids-flo(is) not accurate vids-flt(on_google_map) for the next vids-prw(week)|Number of calls|Google Maps Accuracy|is equal to|average|NONE|week
predict the vids-agg(average) vids-atr(amount_of_calls) by delivery person as he could not find the customers location because the customers vids-flt(location) vids-flo(is) not accurate vids-flt(on_google_map) for the next vids-prw(week)|Number of calls|Google Maps Accuracy|is equal to|average|NONE|week
predict the vids-agg(average) vids-atr(amount_of_phone_calls) made by delivery person where the customer vids-flt(lives_is_in_a_busy_location) for the next vids-prw(week)|Number of calls|Residence in busy location|is equal to|average|NONE|week
I want to know the vids-agg(average) vids-atr(temperature_of_food) where vids-flt(quantity_and_delivery_time_is_low) for the next vids-prw(week)|temperature|Low quantity low time|is equal to|average|NONE|week
predict the vids-agg(total) number of vids-ent(order) in delivary medium increased for vids-atr(politeness) of delivery person where the vids-flt(customer) vids-flo(is) vids-flt(job holder) for vids-prw(tomorrow)|Politeness|Occupation|is equal to|total|Order|tomorrow
predict the vids-agg(total) increased vids-ent(order) in delivary medium of vids-atr(fresh_food) where the vids-flt(customer) vids-flo(is) vids-flt(job holder) for vids-prw(tomorrow)|Freshness|Occupation|is equal to|total|Order|tomorrow
predict the vids-agg(total) increased vids-ent(order) in delivary medium of vids-atr(fresh_food) where the vids-flt(customers_monthly_income) vids-flo(is_greater_than) vids-num(two_thousand) for vids-prw(tomorrow)|Freshness|Monthly Income|is_greater_than|total|Order|tomorrow
predict the vids-agg(total) increased vids-ent(order) in delivary medium of vids-atr(teasty_food) where the vids-flt(monthly_income_of_customer) vids-flo(is_greater_than) vids-num(two_thousand) for vids-prw(tomorrow)|Good Taste|Monthly Income|is_greater_than|total|Order|tomorrow
I want to know the vids-agg(average) vids-atr(food_temperature) where the vids-flt(package_quality) vids-flo(is) good for the next vids-prw(week)|temperature|High Quality of package|is equal to|average|Order|week
I want to know the vids-agg(average) vids-atr(rating) on online delivery services where the customers vids-flt(location) vids-flo(is) not accurate vids-flt(on_google_map) for the next vids-prw(week)|Reviews|Google Maps Accuracy|is equal to|average|Order|week
I want to know the vids-agg(average) vids-atr(rating) on online delivery services where the vids-flt(quantity_and_delivery_time_of_food_is_low) for the next vids-prw(week)|Reviews|Low quantity low time|is equal to|average|NONE|week
I want to know the vids-agg(average) vids-atr(rating) on online delivery services where vids-flt(time_required_for_delivary) vids-flo(is_more_than) vids-num(one) hour for the next vids-prw(week)|Reviews|Long delivery time|is_more_than|average|Order|week
Can you help me find the vids-agg(maximum) vids-ent(order) in delivary medium where the customer wants to vids-flt(eat) Italian over the next vids-prw(week)|NONE|Preference(P1)|is equal to|maximum|Order|week
I want to know the vids-agg(average) number of vids-ent(order) in delivary medium where the vids-flt(preferred_cuisine) vids-flo(is) Italian over the next vids-prw(week)|NONE|Preference(P1)|is equal to|average|Order|week
predict the vids-agg(maximum) number of vids-ent(order) in delivary medium where the the user wants to vids-flt(order_online) within vids-prw(tomorrow)|NONE|Medium (P1)|is equal to|maximum|Order|week
predict the vids-agg(average) average amount of vids-ent(order) in delivary medium in the case where the customer will only vids-flt(order_through_phone) over the next vids-prw(two_days)|NONE|Medium (P1)|is equal to|average|Order|days
predict the vids-agg(maximum) number of vids-atr(married_customers) vids-ent(order) in delivary medium where their vids-flt(monthly_income) vids-flo(is_greater_than) vids-num(two_thousand) over the next vids-num(two) vids-prw(weeks)|Marital Status|Monthly Income|is_greater_than|maximum|Order|week
predict the vids-agg(minimum) number of vids-atr(unmarried_customers) vids-ent(order) in delivary medium where the customer’s vids-flt(monthly_income) vids-flo(is_less_than) vids-num(one_thousand) within next vids-num(two) vids-prw(weeks)|Marital Status|Monthly Income|is_less_than|minimum|Order|week
predict the vids-agg(total) number of vids-ent(order) in delivary medium will be reducing over next vids-prw(week) because the foods have vids-atr(poor_quality_of_hygiene) as well as it has some vids-atr(health_concerns)|NONE|Poor Hygiene, Health Concern|is equal to|total|Order|week
I want to know the vids-agg(maximum) vids-atr(mistaken_order) when the customer’s vids-flt(stay_is_lively) over the next few vids-prw(weeks)|Order_placed_by_mistake|Residence in busy location|is equal to|maximum|Order|week
Can you tell me the vids-agg(average) number of vids-atr(wrong_order) where the vids-flt(customer) vids-flo(is_younger_than) vids-num(21) for the next vids-prw(week)|Order_placed_by_mistake|Age|is_less_than|average|Order|week
predict the vids-agg(minimum) number of vids-atr(wrongfully_submitted_order) where the vids-flt(customer’s_age) vids-flo(is_less_than) vids-num(21) for the next vids-prw(week)|Order_placed_by_mistake|Age|is_less_than|minimum|Order|week
predict the vids-agg(average) number of vids-atr(items_missing) in each vids-ent(order) in delivary medium where the vids-flt(customer’s_gender) vids-flo(is) female over the next few vids-prw(weeks)|Missing item|Gender|is equal to|average|Order|week
predict the vids-agg(maximum) number of vids-atr(wrong_order) for vids-prw(tomorrow) where the vids-flt(customer) vids-flo(is) vids-flt(in_corporate_job)|Order_placed_by_mistake|Occupation|is equal to|maximum|Order|week
Help me find the vids-agg(total) number of order with vids-atr(customers_location_placed_on_map_accurately) where he has vids-flt(high_education_qualification) over the next two vids-prw(weeks)|Google Maps Accuracy|Educational Qualifications|is equal to|total|Order|weeks
predict the vids-agg(maximum) number of vids-atr(high_quality_food) vids-ent(ordered) where the customers vids-flt(family) vids-flo(has_more_than) vids-num(four) members|Good Food quality|Family size|is_more_than|maximum|Order|NONE
I want to know the vids-agg(maximum) vids-ent(order) in delivary medium vids-atr(placed_online) where the vids-flt(customer) vids-flo(is_older_than) vids-num(40) over the next vids-prw(week)|Medium (P1)|Age|is_more_than|maximum|Order|week
Help me find the vids-agg(total) vids-atr(online) vids-ent(orders) where the customer will want to have vids-flt(family_size_meal) over the next vids-prw(week)|Medium (P1)|Meal (P1)|is equal to|total|Order|week
predict the vids-agg(average) vids-ent(order) in delivary medium where the customer vids-flo(wants_to_have) Italian food for the next vids-prw(week)|NONE|Preference(P1)|is equal to|average|Order|week
Help me find the vids-agg(maximum) vids-ent(order) in delivary medium where vids-flt(online_order_is_easy) for the next vids-prw(week)|NONE|Ease and convenient|is equal to|maximum|Order|week
Help me find the vids-agg(maximum) number of vids-ent(order) in delivary medium where vids-flt(resturant_option) vids-flo(is_more_than) vids-num(three) for the next vids-prw(week)|NONE|More restaurant choices|is_more_than|maximum|Order|week
I want to know the vids-agg(maximum) number of vids-atr(discount) vids-ent(orders) where the vids-flt(customer’s_age) vids-flo(is_less_than) vids-num(21) for the next vids-prw(week)|More Offers and Discount|Age|is_less_than|maximum|Order|week
predict the vids-agg(maximum) delivered vids-ent(order) in delivary medium with the delivery system having a vids-atr(good_tracking_system) where vids-flt(age_of_customer) vids-flo(is_more_than) 30 within next vids-prw(week)|Good Tracking system|Age|is_more_than|maximum|Order|week
I want to know the vids-agg(maximum) number of vids-ent(order) in delivary medium reduced because the customer vids-atr(likes_cooking) where the vids-flt(family_size) of the customer vids-flo(is_more_than) vids-num(four) within next vids-prw(week)|Self Cooking|Family size|is_more_than|maximum|Order|week
predict the vids-agg(maximum) number of vids-ent(order) in delivary medium reduced for the vids-atr(health_concern) about the food where the customer’s vids-flt(family_size) vids-flo(is) big over next vids-prw(week)|Health Concern|Family size|is_equal_to|maximum|Order|week
predict the vids-agg(maximum) number of vids-ent(order) in delivary medium will get cancelled for vids-atr(late_delivary) by the carrier where the vids-flt(customer’s_age) vids-flo(is_more_than) vids-num(21) for the next vids-prw(week)|Late Delivery|Age|is_more_than|maximum|Order|week
I want to know the vids-agg(mean) number of vids-ent(order) in delivary medium has been decreased because of vids-atr(poor_hygiene) of the food where the vids-flt(customer_is_in_corporate_job) for vids-prw(tomorrow)|Poor Hygiene|Occupation|is equal to|mean|Order|tomorrow
predict the vids-agg(mean) amount of vids-ent(order) in delivary medium will be decreasing for the customer’s vids-atr(bad_experience) with the delivery person where the customer vids-flo(is) vids-flt(highly_educated) over the next vids-prw(week)|Bad past experience|Educational Qualifications|is equal to|maximum|Order|week
Can you help me find the vids-agg(maximum) number of vids-ent(order) in delivary medium will be lessened because of the vids-atr(unavailability) of appetizer in the restaurant where the customer vids-flo(is) vids-flt(business_person) over the next vids-prw(week)|unavailability|Occupation|is_equal_to|maximum|Order|week
I want to know the vids-agg(maximum) number of vids-ent(order) in delivary medium will be reduced because of vids-atr(increased_food_price) where the vids-flt(age_of_a_customer) vids-flo(is_less_than) vids-num(18) for the next vids-prw(week)|Unaffordable|Age|is_less_than|maximum|Order|week
I want to know the vids-agg(max) vids-atr(delay_caused_by_delivary_assignment) where the customer vids-flt(is_in_capital) for the next vids-prw(week)|Delay of delivery person getting assigned|Residence in busy location|is equal to|maximum|Order|week
predict the vids-agg(maximum) vids-atr(food_pick_up_delay) where the customer vids-flt(lives_in_big_city) for the next vids-prw(week)|Delay of delivery person picking up food|Residence in busy location|is equal to|maximum|Order|week
predict the vids-agg(maximum) vids-atr(delay_caused_by_delivary_assignment) where the customers vids-flt(location) vids-flo(is) not vids-flt(accurate_on_map) for the next vids-prw(week)|Delay of delivery person getting assigned|Google Maps Accuracy|is equal to|maximum|Order|week
I want to know the vids-agg(maximum) vids-atr(food_pick_up_delay) where the vids-flt(delivery_persons) vids-flo(is) vids-flt(new_to_job) for the next vids-prw(week)|Delay of delivery person picking up food|Delivery person ability|is equal to|maximum|Order|week
predict the vids-agg(average) number of vids-ent(order) in delivary medium will get a vids-atr(good_reviews) where the vids-flt(road_condition) from restaurant and customer’s house vids-flo(is) good for the next vids-prw(week)|Reviews|Good Road Condition|is equal to|maximum|Order|week
predict the vids-agg(latest) vids-atr(time_of_order) at night where the vids-flt(traffic_condition) of the customer’s living area vids-flo(is) very busy over the next vids-prw(week)|Order Time|Good Road Condition|is equal to|maximum|Order|week
Can you help me find the vids-agg(latest) vids-ent(order) time in delivary medium vids-atr(at_night) where the ordered food vids-flt(quantity_and_delivery_time_both_are_low) for the next vids-prw(week)|Order Time|Low quantity low time|is equal to|maximum|Order|week