I'm trying fit my data , but I couldn't fit it.Data set0.50,00.75,01.00,01.25,01.50,01.75,01.75,12.00,02.25,12.50,02.75,13.00,03.25,13.50,04.00,14.25,14.50,14.75,15.00,15.50,1and my code data = np.loadtxt('dat', delimiter=',',dtype=None);x=data[:,0:1];y=data[:,1].reshape(x.size/x[0].size,1);a=np.ones(shape=(y.size,x[0].size+1));a[:,1:2]=x;q=np.ones(shape=(a.shape[1],1));alpha=0.003for i in range(500000):    h=1/(1+np.exp(-np.dot(a,q)))    for j in range(q.size):        q[j][0]=q[j][0]-alpha*np.sum((h-y)*a[:,j]);plt.axis((-1,10,-1,5))plt.plot(x,y,'x',x,h);plt.show();So I tried different learning rates(alpha),tried different number of iterations but my fitting data is looking like this but it's should looks like this enter link description hereWhat am I missing? Is there any logical error or something like that? Thanks for your deal.
Logistic Regression can't fit my data
machine learning;python;logistic regression