In [1]:

    

import pandas as pd
import solution


    

In [2]:

    

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
%matplotlib inline


    

In [3]:

    

train = solution.get_data()
test = pd.DataFrame(
    [
        [0.05, 0.54],
        [0.91, 0.91],
        [0.31, 0.76],
        [0.51, 0.31],
    ]
)


    

In [4]:

    

for s in solution.solve(train, test):
    print s


    

    




180.376824425
1312.06505966
440.129253298
343.715380076

In [6]:

    

model_dict = solution.get_poly_models(train[:60])


    

In [7]:

    

solution.plot_poly_models(train[60:], model_dict)


    

In [8]:

    

def plot_3d(df):
    td = plt.figure(figsize=(10, 10)).gca(projection='3d')
    td.scatter(df[0], df[1], df[2])
    td.set_xlabel('feature_1')
    td.set_ylabel('feature_2')
    td.set_zlabel('price')
    plt.show()


    

In [10]:

    

plot_3d(train)


    

In [13]:

    

for i in range(1, 6):
    print i, solution.validate_k_fold(train, i)


    

    




1 8188.92775594
2 115.777100985
3 22.9791315152
4 27.5994842464
5 43.0676324532