This model was built using BigML, and historical data for punk valuations. Input the punk gender and attributes, and the model will predict the % above or below the 30 day median sale price. For example, if the median price of a cryptopunk is 25 ETH, and the model predicts a punk to be worth 150% of median, then the estimated value is 37.5 ETH.
# Requires BigML Python bindings
#
# Install via: pip install bigml
#
# or clone it:
# git clone https://github.com/bigmlcom/python.git
from bigml.linear import LinearRegression
from bigml.api import BigML
# Downloads and generates a local version of the linear regression,
# if it hasn't been downloaded previously.
linearregression = LinearRegression('linearregression/605116b3fb7bdd342a0003f1',
api=BigML("jas225",
"cf1da34fd276cc47cff75bfc06365202a0fadbc2",
domain="bigml.io"))
# To make predictions fill the desired input_data
# in next line. All fields are compulsory if they don't have
# missing values.
input_data = {
"Attributes": "Earring",
"Gender": "Male"
}
linearregression.predict(input_data)