text_plain_output_1.png
from subprocess import check_output

"""
So I want to test some transformations and changes to the modelling data:
** for each of the below get it running on 5% then validate on 20% modelling data)
(1) Try Different combinations of "resizing data" 
(2) Try "Resampling approach" in pre-processing
(3) Try all of the transformations below on pixel array and MXNET transformed features
        reciprocal   t = 1 / x           
        log base 10  t = log_10 x         
        10 to the power  x = 10^t
        log base e   t = log_e x = ln x  
        e to the power   x = exp(t)
        log base 2   t = log_2 x          
        2 to the power   x = 2^t 
        cube root    t = x^(1/3)          
        cube             x = t^3
        square root  t = x^(1/2)          
        square           x = t^2
        (data.dat$Y)^(1/9) Takes the ninth root of Y
        abs(data.dat$Y) Finds the absolute value of Y
        ** Try all known trigonometric functions **
        sin(data.dat$Y) Calculates the sine of Y
        asin(data.dat$Y) Calculates the inverse sine (arcsine) of Y
(4) Try Masking all images
    then try all transformation in (3)
(5) Try dropping all columns with no useful information
"""
import numpy as np
import pandas as pd
from subprocess import check_output
print(check_output(['ls', '../input']).decode('utf8'))