import pandas as pd
import numpy as np
from sklearn import preprocessing, cross_validation, neighbors, svm
import matplotlib.pyplot as plt

#Read Data
df = pd.read_csv("poker.txt")
full_data = df.astype(float).values.tolist()

X = np.array(df.drop([df.columns[10]], 1))
y = np.array(df[df.columns[10]])
X_train, X_test, y_train, y_test = cross_validation.train_test_split(X, y, test_size = 0.4)

svc = svm.SVC(kernel='poly', C=1, decision_function_shape='ovr').fit(X, y)
confidence = svc.score(X_test, y_test)
print(confidence)