add SVM related stuff

Author: tmp-coder

CMU-ML/10701/HW1_Tex_v3/F16_10701_HW1_v3.pdf

@@ -0,0 +1,21 @@
+import numpy as np
+
+
+def gen_synthetic(n,p,sigma):
+    
+    #Generate X0
+    X=np.random.normal(size=(n,p))
+    print ("X0 generated")
+    
+    w=np.random.uniform(size=(p,1))-0.5
+    print ("w generated")
+    
+    
+    Y0 = np.dot(X,w) 
+    Y0 = Y0+np.random.normal(loc=0,scale=sigma,size=(n,1))
+    
+    Y = np.ones((n,1))
+    Y[Y0<0]=-1
+    Y[Y0>=0]=1
+    
+    return X,Y

CMU-ML/10701/HW1_Tex_v3/gen_synthetic.py

@@ -0,0 +1,10 @@
+generate_synthetic_data <- function(n,p,sigma){
+  X <-matrix(rnorm(n*p),n)
+  w <- matrix(rnorm(p),p)-0.5
+  Y0 <- X %*% w
+  temp <- matrix(rnorm(n,mean=0,sd=sigma))
+  Y0 <- Y0 + temp
+  
+  Y <- matrix(rep(1,n),n)
+  Y[Y0<0] = -1
+}

CMU-ML/10701/HW1_Tex_v3/gen_synthetic_data.R

@@ -0,0 +1,7 @@
+function [Y,X] = gen_synthetic_data(n,p,sigma)
+    X = randn(n,p);
+    w = rand(p,1) -0.5;
+    Y0 = X * w + normrnd(0,sigma,n,1);
+    Y = ones(n,1);
+    Y(Y0<0) = -1;
+end