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leesideas edited this page Feb 12, 2025 · 29 revisions

Description

Input features

Field name Type Example Description Used for Importance
property_sub_type string 'SingleFamilyResidence' Building structure type of home. Accepted values are 'Apartment', 'SingleFamilyResidence', 'Townhouse', 'Duplex', 'Terraced', 'Cabin', 'Farm' All Necessary
occupant_type string 'Owner' Ownership type of home. Accepted values are 'Owner', 'TenantOwnership' All Necessary
living_area int 75 Living area of home in square meters All Necessary
lot_size_area int 1000 Lot area in square meters All houses Low
secondary_area int 40 Secondary area of home in square meters All houses Medium
rooms_total int 4 Number of rooms in home Apartment Low
association_fee int 3500 Monthly co-operation member fee occupant_type = TenantOwnership Medium
year_built int 1950 Building construction year All High
latitude decimal 59.405589 Latitude of current residence All Necessary
longitude decimal 18.323536 Longitude of current residence All Necessary
valuation_date string '2024-01-14' Usually left empty. Specifies the date on which the valuation occurs. Note that the transactions that the valuations are based on are timestamped on the purchase contract date. All Optional

Note on Importance

A general measurement of the importance of the variable for the valuation model. Note that something with "low" importance can still be very important in some cases. Our recommendation is to include all information.

Note on property_sub_type

We follow the RESO standard to the largest possible extent. However, the Swedish house types "kedjehus" ('chain house') and "radhus" ('row house') are not separated in the RESO standard. We use 'Terraced' for "kedjehus" and 'Townhouse' for "radhus". The difference is that for a "kedjehus" there is a building, usually a garage, between the houses that is connecting them.

Notes on occupant_type

For apartments, you can assume that the occupant_type is 'TenantOwnership'. The model does not perform valuations on apartments with ownership and it does not handle rental apartments. If you would try to do a valuation on a rental apartment, it would be treated as tenant ownership.

For 'SingleFamilyResidence' and 'Duplex', you can assume that occupant_type is "Owner". However, there are some rare cases where these types of houses are tenant ownerships.

At the moment, we treat houses on land leaseholds as "Owner". In general, the model will overestimate the valuations of land leaseholds. This error will likely be small due to low lease amounts in Sweden.

Data validation

This is our recommended settings. Note that homes with extreme values are likely to not get a valuation. The min and max values in the table below are meant to avoid typing mistakes and entering information that the API cannot handle.

Parameter min max
living_area 15 600
lot_size_area 50 30000
secondary_area 0 500
rooms_total 1 20
association_fee 0 25 000
year_built 1500 'current year'
  • Note: All values are integers! Decimals are not allowed at the moment.
  • Note: Do NOT use "0" as missing value! 0 is a valid value for association fee and secondary area. Use Null or do not send the parameter.

Model Usage

SDK

import realai 
import pandas as pd

realai_client = realai.Client()
# Login
realai_client.authenticate("USER","PASSWORD")

# Perform inference and get the predicted value
result = realai_client.avm(input_features={
					  "property_sub_type": "SingleFamilyResidence",
					  "living_area": 150,
					  "lot_size_area": 32,
					  "secondary_area": None,
					  "rooms_total": 3,
					  "valuation_date": "2022-04-01",
					  "latitude": 59.405589084302875,
					  "longitude": 18.32353631202982,
					  "occupant_type": "Owner",
					  "association_fee": None,
					  "year_built": 1992
				   })


# Print the predicted probability of moving
print("Predicted Value of Home:", result['pred'])

Raw version

curl --location --request POST  'https://api.modelmarket.io/v1/models/normal/realai/avm' \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer <ACCESS_TOKEN>' \
--data '{"property_sub_type":"SingleFamilyResidence",
      "living_area":150.0,
      "lot_size_area":32,
      "secondary_area":null,
      "rooms_total":3,
      "valuation_date":"2022-04-01",
      "latitude":59.405589084302875,
      "longitude":18.32353631202982,
      "occupant_type":"Owner",
      "association_fee":null,
      "year_built":1992}'

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