neingeist
/
coursera-ml-007-exercises
Archived
1
0
Fork 0
Code Releases Activity

Random initialization

Browse Source
master
neingeist 10 years ago
parent 863f1d7157
commit 052f0625c3
1 changed files with 6 additions and 11 deletions
Show Stats Download Patch File Download Diff File

17
ex4/randInitializeWeights.m
Unescape Escape View File

@ -1,15 +1,15 @@
function W = randInitializeWeights(L_in, L_out)
%RANDINITIALIZEWEIGHTS Randomly initialize the weights of a layer with L_in
%incoming connections and L_out outgoing connections
% W = RANDINITIALIZEWEIGHTS(L_in, L_out) randomly initializes the weights
% of a layer with L_in incoming connections and L_out outgoing
% connections.
% W = RANDINITIALIZEWEIGHTS(L_in, L_out) randomly initializes the weights
% of a layer with L_in incoming connections and L_out outgoing
% connections.
%
% Note that W should be set to a matrix of size(L_out, 1 + L_in) as
% the column row of W handles the "bias" terms
%
% You need to return the following variables correctly
% You need to return the following variables correctly
W = zeros(L_out, 1 + L_in);
% ====================== YOUR CODE HERE ======================
@ -19,13 +19,8 @@ W = zeros(L_out, 1 + L_in);
% Note: The first row of W corresponds to the parameters for the bias units
%
epsilon_init = 0.12;
W = rand(L_out, 1 + L_in) * 2 * epsilon_init - epsilon_init;
% =========================================================================