Decision Tree in R Language

I have been training Yelp Data for generating a few results from it, I have applied the Decission Tree Algotrithm on my data but I am still not able to understand the result. Can any one explain decision tree results below:

  1. business_attributes_Caters <= 0; criterion = 1, statistic = 61.809
  2. business_attributes_GoodForMeal_dinner <= 0; criterion = 1, statistic = 47.862
  3. business_attributes_GoodForMeal_brunch <= 0; criterion = 0.999, statistic = 25.125
  4. business_attributes_BusinessParking_street <= 0; criterion = 0.984, statistic = 19.844
    5)* weights = 257
  5. business_attributes_BusinessParking_street > 0
    6)* weights = 65
  6. business_attributes_GoodForMeal_brunch > 0
    7)* weights = 89
  7. business_attributes_GoodForMeal_dinner > 0
  8. business_attributes_GoodForKids <= 0; criterion = 0.955, statistic = 17.615
  9. business_attributes_RestaurantsGoodForGroups <= 0; criterion = 0.983, statistic = 19.725
    10)* weights = 7
  10. business_attributes_RestaurantsGoodForGroups > 0
    11)* weights = 130
  11. business_attributes_GoodForKids > 0
  12. business_attributes_Ambience_trendy <= 0; criterion = 0.997, statistic = 23.476
  13. business_attributes_BusinessParking_garage <= 0; criterion = 0.987, statistic = 20.451
    14)* weights = 408
  14. business_attributes_BusinessParking_garage > 0
    15)* weights = 43