@@ -663,35 +663,47 @@
},
{
"cell_type" : " code"
"execution_count" : 479 ,
"execution_count" : 496 ,
"metadata" : {},
"outputs" : [
{
"data" : {
"text/plain" : [
" array([2, 3, 4])"
]
},
"execution_count" : 479 ,
"metadata" : {},
"output_type" : " execute_result"
}
],
"outputs" : [],
"source" : [
" a1 = np.array([1,2,3])\n "
" a2 = np.array([2,3,4])\n "
" a1+1"
" #So if MSE doesnt improve stop??\n "
" #TF recommends running without threshold, plotting change in MSEs, and then deciding a good threshold from that\n "
" \n "
" def der_loss(y_function, weights, )\n "
" \n "
" \n "
" \n "
" threshold = 0.0000001 #difference in MSE \n "
" learn = 0.01 #learning rate\n "
" delta = 0.1\n "
" max_iters = 1000\n "
" \n "
" def gradient_descent(y_function, weight_guess, max_iters, learn)\n "
" weight_list = [weight_guess]\n "
" iters = 0 \n "
" w_n_prev = weight_guess\n "
" \n "
" while iters < max_iter:\n "
" gradient_eval = der_loss(y_function, w_n_prev) #evaluate gradient\n "
" w_n = w_prev + learn*gradient_eval #get new weights and bias\n "
" y_eval = y_function(*w_n)\n "
" \n "
" weight_list.append(w_n)\n "
" \n "
" w_n_prev = w_n\n "
" \n "
" iters+=1 #before or after threshold check?????\n "
" \n "
" if abs(y_eval - y_function(*weight_list[step-1])) < threshold: break\n "
]
},
{
"cell_type" : " code"
"execution_count" : 496 ,
"execution_count" : null ,
"metadata" : {},
"outputs" : [],
"source" : [
" #So if MSE doesnt improve stop??\n "
" #TF recommends running without threshold, plotting change in MSEs, and then deciding a good threshold from that\n "
" \n "
" #not necessarily right, should not have delta or something\n "
" def get_new_weights(old_weights, learning, delta, y_function, y_true):\n "
" y_old_pred = y_function(*old_weights)\n "
@@ -703,17 +715,7 @@
" \n "
" change = learning*((mse_delta - mse_old)/delta)\n "
" \n "
" return old_weights - change #new weights \n "
" \n "
" \n "
" threshold = 0.0000001 #difference in MSE \n "
" learn = 0.01 #learning rate\n "
" delta = 0.1\n "
" iters = 0 \n "
" max_iters = 1000\n "
" \n "
" while iters < max_iter:\n "
" iters+=1"
" return old_weights - change #new weights "
]
},
{
@@ -1255,13 +1257,6 @@
" return df_train, df_test"
]
},
{
"cell_type" : " markdown"
"metadata" : {},
"source" : [
" Discuss why we normalize..."
]
},
{
"cell_type" : " code"
"execution_count" : 461 ,