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