A machine learning model for cryptopunk valuation (DRAFT)

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)