diff --git a/libsvm/svm.py b/libsvm/svm.py
old mode 100644
new mode 100755
index 0359cd9..aa51ab4
--- a/libsvm/svm.py
+++ b/libsvm/svm.py
@@ -3,6 +3,7 @@
 import sys
 from ctypes import *
 from os import path, listdir, pardir
+import numpy as np
 
 try:
     import scipy
@@ -80,15 +81,15 @@ def gen_svm_nodearray(xi, feature_max=None, isKernel=False):
 
     xi_shift = 0  # ensure correct indices of xi
     if scipy and isinstance(xi, tuple) and len(xi) == 2 \
-            and isinstance(xi[0], scipy.ndarray) and isinstance(xi[1],
-                                                                scipy.ndarray):  # for a sparse vector
+            and isinstance(xi[0], np.ndarray) and isinstance(xi[1],
+                                                                np.ndarray):  # for a sparse vector
         if not isKernel:
             index_range = xi[0] + 1  # index starts from 1
         else:
             index_range = xi[0]  # index starts from 0 for precomputed kernel
         if feature_max:
             index_range = index_range[scipy.where(index_range <= feature_max)]
-    elif scipy and isinstance(xi, scipy.ndarray):
+    elif scipy and isinstance(xi, np.ndarray):
         if not isKernel:
             xi_shift = 1
             index_range = xi.nonzero()[0] + 1  # index starts from 1
@@ -120,8 +121,8 @@ def gen_svm_nodearray(xi, feature_max=None, isKernel=False):
     ret[-1].index = -1
 
     if scipy and isinstance(xi, tuple) and len(xi) == 2 \
-            and isinstance(xi[0], scipy.ndarray) and isinstance(xi[1],
-                                                                scipy.ndarray):  # for a sparse vector
+            and isinstance(xi[0], np.ndarray) and isinstance(xi[1],
+                                                                np.ndarray):  # for a sparse vector
         for idx, j in enumerate(index_range):
             ret[idx].index = j
             ret[idx].value = (xi[1])[idx]
@@ -192,16 +193,16 @@ class svm_problem(Structure):
     _fields_ = genFields(_names, _types)
 
     def __init__(self, y, x, isKernel=False):
-        if (not isinstance(y, (list, tuple))) and (not (scipy and isinstance(y, scipy.ndarray))):
+        if (not isinstance(y, (list, tuple))) and (not (scipy and isinstance(y, np.ndarray))):
             raise TypeError("type of y: {0} is not supported!".format(type(y)))
 
         if isinstance(x, (list, tuple)):
             if len(y) != len(x):
                 raise ValueError("len(y) != len(x)")
-        elif scipy != None and isinstance(x, (scipy.ndarray, sparse.spmatrix)):
+        elif scipy != None and isinstance(x, (np.ndarray, sparse.spmatrix)):
             if len(y) != x.shape[0]:
                 raise ValueError("len(y) != len(x)")
-            if isinstance(x, scipy.ndarray):
+            if isinstance(x, np.ndarray):
                 x = scipy.ascontiguousarray(x)  # enforce row-major
             if isinstance(x, sparse.spmatrix):
                 x = x.tocsr()
@@ -223,7 +224,7 @@ def __init__(self, y, x, isKernel=False):
         self.n = max_idx
 
         self.y = (c_double * l)()
-        if scipy != None and isinstance(y, scipy.ndarray):
+        if scipy != None and isinstance(y, np.ndarray):
             scipy.ctypeslib.as_array(self.y, (self.l,))[:] = y
         else:
             for i, yi in enumerate(y): self.y[i] = yi