def main():
data = pd.read_csv('lexample.csv')
W0 = ndl.ndl(data)
diff = np.zeros_like(W0)
for i in xrange(10):
W = ndl.rw(data, M=10000)
diff += abs(W - W0)
diff = diff / 10.
print diff.max(), diff.min(), np.mean(diff)
def accuracy(self, M):
W = ndl.rw(self.data, M=M)
A = self.activation(W)
return np.mean(A.idxmax(1) == self.data['Outcomes'])
def accuracy(self,M):
W = ndl.rw(self.data, distribution=self.distribution, M=M)
A = self.activation(W)
return np.mean(A.idxmax(1) == self.data['Outcomes'])
def simulate(i):
global data
W = ndl.rw(data, M=1000000)
return i, W
def simulate(i):
global data
W = ndl.rw(data,M=1000000)
return i,W
