text_plain_output_2.png application_vnd.jupyter.stderr_output_1.png image_output_1.png
from subprocess import check_output

import pandas as pd
import numpy as np
import random as rnd
import sklearn.linear_model
import sklearn.svm
import sklearn.ensemble
import sklearn.neighbors
import sklearn.naive_bayes
import sklearn.tree
import sklearn.neural_network
from subprocess import check_output
import seaborn as sns
import matplotlib.pyplot as plt
import os
train_set_size = 891
valid_set_size = 0
print(os.path.dirname(os.getcwd()) + ':', os.listdir(os.path.dirname(os.getcwd())))
print(os.getcwd() + ':', os.listdir(os.getcwd()))