PranavSharma/dynamic-pricing-model

1{2    "sklearn": {3        "columns": [4            "Number_of_Riders",5            "Number_of_Drivers",6            "Location_Category",7            "Customer_Loyalty_Status",8            "Number_of_Past_Rides",9            "Average_Ratings",10            "Time_of_Booking",11            "Vehicle_Type",12            "Expected_Ride_Duration",13            "Historical_Cost_of_Ride"14        ],15        "environment": [16            "scikit-learn"17        ],18        "example_input": {19            "Average_Ratings": [20                4.47,21                4.06,22                3.9923            ],24            "Customer_Loyalty_Status": [25                "Silver",26                "Silver",27                "Silver"28            ],29            "Expected_Ride_Duration": [30                90,31                43,32                7633            ],34            "Historical_Cost_of_Ride": [35                284.25727302188227,36                173.87475274940766,37                329.795468962246638            ],39            "Location_Category": [40                "Urban",41                "Suburban",42                "Rural"43            ],44            "Number_of_Drivers": [45                45,46                39,47                3148            ],49            "Number_of_Past_Rides": [50                13,51                72,52                053            ],54            "Number_of_Riders": [55                90,56                58,57                4258            ],59            "Time_of_Booking": [60                "Night",61                "Evening",62                "Afternoon"63            ],64            "Vehicle_Type": [65                "Premium",66                "Economy",67                "Premium"68            ]69        },70        "model": {71            "file": "best_model.pkl"72        },73        "model_format": "pickle",74        "task": "tabular-regression"75    }76}