Digit recognition using python

I am doing digit recognition program using python.this following code is to perform recognition.The program is taken from "http://hanzratech.in/2015/02/24/handwritten-digit-recognition-using-opencv-sklearn-and-python.html".

# Import the modules
import cv2
from sklearn.externals import joblib
from skimage.feature import hog
import numpy as np

# Load the classifier
clf = joblib.load("digits_cls.pkl")

# Read the input image 
im = cv2.imread("photo_2.jpg")

# Convert to grayscale and apply Gaussian filtering
im_gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
im_gray = cv2.GaussianBlur(im_gray, (5, 5), 0)

# Threshold the image
ret, im_th = cv2.threshold(im_gray, 90, 255, cv2.THRESH_BINARY_INV)

# Find contours in the image
_, ctrs, hier = cv2.findContours(im_th.copy(), cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
# Get rectangles contains each contour
rects = [cv2.boundingRect(ctr) for ctr in ctrs]

# For each rectangular region, calculate HOG features and predict
# the digit using Linear SVM.
for rect in rects:
# Draw the rectangles
cv2.rectangle(im, (rect[0], rect[1]), (rect[0] + rect[2], rect[1] +rect[3]), (0, 255, 0), 3) 
# Make the rectangular region around the digit
leng = int(rect[3] * 1.6)
pt1 = int(rect[1] + rect[3] // 2 - leng // 2)
pt2 = int(rect[0] + rect[2] // 2 - leng // 2)
roi = im_th[pt1:pt1+leng, pt2:pt2+leng]
# Resize the image
roi = cv2.resize(roi, (28, 28), interpolation=cv2.INTER_AREA)
roi = cv2.dilate(roi, (3, 3))
# Calculate the HOG features
roi_hog_fd = hog(roi, orientations=9, pixels_per_cell=(14, 14),cells_per_block=(1, 1), visualise=False)
nbr = clf.predict(np.array([roi_hog_fd], 'float64'))
cv2.putText(im, str(int(nbr[0])), (rect[0],rect[1]),cv2.FONT_HERSHEY_DUPLEX, 2, (0, 255, 255), 3)

cv2.imshow("Resulting Image with Rectangular ROIs", im)
cv2.waitKey()

But i am getting error:-

C:UsersuserDesktopNew folderNew folderdigitRecognitiondigitRecognition>python performRecognition.py
Traceback (most recent call last):
File "performRecognition.py", line 40, in <module>
nbr = clf.predict(np.array([roi_hog_fd], 'float64'))
File "C:UsersuserAnaconda2libsite-packagessklearnlinear_modelbase.py", line 273, in predict
return self.classes_[indices]
AttributeError: 'LinearSVC' object has no attribute 'classes_'

I also have a trainer program but by running it .It crashes the command prompt.