from sklearn import linear_model
from sklearn.metrics import r2_score, mean_squared_error
from sklearn.neighbors import KNeighborsClassifier
import numpy as np
import matplotlib.pyplot as plt

### x
testx = open("test.txt")
testx.readline()
Xtest= np.loadtxt(testx)
print (Xtest.shape)


### target x
targetx = open("testTargett.txt")
targetx.readline()
Xtarget = np.loadtxt(targetx)
print (datasettargettrain.shape)

### y
train = open("forecast.txt")
train.readline()
datasettrain = np.loadtxt(train)
print (datasettrain.shape)

### target y
traintarget = open("TICTGTS2000.txt")
traintarget.readline()
targetTrain = np.loadtxt(traintarget)
print (targetTrain.shape)


x = Xtest
targetX = x[:, 85]
y = datasettrain
targetY = datasettargettrain