forked from aelgabli/GADMM
-
Notifications
You must be signed in to change notification settings - Fork 0
/
LogisticRegression_Synthetic.m
277 lines (214 loc) · 7.53 KB
/
LogisticRegression_Synthetic.m
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
clear
close all
%% data allocation for linear regression
% [Xdata_29] = load('data2/data.txt'); % ionosphere dataset
% [ydata_29] = load('data2/y.txt');
% [Xdata_29] = load('data9/data.txt'); % adult dataset
% [ydata_29] = load('data9/y.txt');
[Xdata_29] = load('data11/data.txt'); % derm dataset
[ydata_29] = load('data11/y.txt');
num_iter1=100000;
num_iter=num_iter1;
accuracy=1E-4;
num_workers=24;
X=cell(num_workers);
y=cell(num_workers);
num_feature=size(Xdata_29(1:50,:),2);
num_sample=size(Xdata_29(1:50,:),1);
Xdata=randn(num_sample,num_feature);
ydata=[ydata_29(1:50)];
[Q R]=qr(Xdata);
diagmatrix=diag(ones(num_sample,1));
% [lambda]=eig(Xdata'*Xdata);
%Hmax=zeros(num_workers,1);
for i=1:num_workers
X{i}=1^(i-1)*Q(:,i)*Q(:,i)'+diag(ones(num_sample,1));
%Hmax(i)=max(eig(X{i}'*X{i}));
y{i}=ydata;
end
num_feature=size(X{1},2);
%Hmax_sum=sum(Hmax);
lambda=0.001;
lambda=0.00001;
Hmax=zeros(num_workers,1);
for i=1:num_workers
Hmax(i)=0.25*max(abs(eig(X{i}'*X{i})))+lambda;
end
%% data pre-analysis for GD and LAG algorithms that we compare with
%lambda=0;
X_fede=[];
y_fede=[];
for i=1:num_workers
X_fede=[X_fede;X{i}];
y_fede=[y_fede;y{i}];
end
%% Optimal solution
XX=X_fede;
YY=y_fede;
%size = num_feature;
%obj0 = opt_sol_logistic(XX,YY, num_feature, lambda, num_workers);%(0.5*sum_square(XX*z1 - YY));
%opt_obj = obj0*ones(1,num_iter);
%% GD, DGD, LAG
[obj_GD, loss_GD, time_GD, obj_DGD, loss_DGD, time_DGD,...
obj_LAG_PS, loss_LAG_PS, time_lagPS, comm_iter_final_LAG_PS,...
obj_LAG_WK, loss_LAG_WK, time_lagWK, comm_iter_final_LAG_WK,...
obj_cyclic_IAG, loss_cyclic_IAG, obj_R_IAG, loss_R_IAG, stepsize2, obj0]=GD_DGD_LAG_logistic(X,y, num_workers, num_feature, Hmax, num_iter, X_fede, y_fede, num_sample, lambda, accuracy);
%obj0=obj1;
%% Dual Averaging
acc = accuracy;%1E-3;
[obj_dualAvg, loss_dualAvg, Iter_dualAvg, dualAvg_time]=dual_averaging_logisticReg(X_fede,y_fede, num_workers, num_feature, num_sample, num_iter, obj0, acc, stepsize2, lambda);
%% GADMM
num_iter=400;
gdStep=2.2;%2.5;
acc = 1E-4;%accuracy;%1E-3;
rho=0.0003;
%rho=0.0300;
[obj_GADMM_rho0003, loss_GADMM_rho0003, Iter_0003, gadmm_time0003] = group_ADMM_logistic_GD(X_fede,y_fede, rho, num_workers, num_feature, num_sample, num_iter, obj0, lambda, acc, gdStep);
rho
rho=0.0002;
[obj_GADMM_rho0002, loss_GADMM_rho0002, Iter_0002, gadmm_time0002] = group_ADMM_logistic_GD(X_fede,y_fede, rho, num_workers, num_feature, num_sample, num_iter, obj0, lambda, acc, gdStep);
rho
num_iter=num_iter1;
%num_iter = 40000;
for iter=1:num_iter
cumulative_com_GD(iter)=iter*num_workers+iter;
%errorPer_GD(iter) = abs(loss_GD(iter)/opt_obj(iter)*100);
end
for iter=1:num_iter
cumulative_com_DGD(iter)=iter*num_workers;
%errorPer_GD(iter) = abs(loss_GD(iter)/opt_obj(iter)*100);
end
for iter=1:length(comm_iter_final_LAG_PS)
cumulative_com_LAG_PS(iter)=comm_iter_final_LAG_PS(iter)+iter;
%errorPer_LAG_PS(iter) = abs(loss_LAG_PS(iter)/opt_obj(iter)*100);
end
for iter=1:length(comm_iter_final_LAG_WK)
cumulative_com_LAG_WK(iter)=comm_iter_final_LAG_WK(iter)+iter;
%errorPer_LAG_WK(iter) = abs(loss_LAG_WK(iter)/opt_obj(iter)*100);
end
num_iter=Iter_dualAvg;
for iter=1:num_iter
cumulative_com_dualAvg(iter)=iter*num_workers;
%errorPer_GADMM_rho3(iter) = abs(loss_GADMM_rho3(iter)/opt_obj(iter)*100);
end
num_iter=Iter_0003;
for iter=1:num_iter
cumulative_com_GADMM_rho0003(iter)=iter*num_workers;
%errorPer_GADMM_rho3(iter) = abs(loss_GADMM_rho3(iter)/opt_obj(iter)*100);
end
num_iter=Iter_0002;
for iter=1:num_iter
cumulative_com_GADMM_rho0002(iter)=iter*num_workers;
%errorPer_GADMM_rho5(iter) = abs(loss_GADMM_rho5(iter)/opt_obj(iter)*100);
end
figure(2);
subplot(1,3,1);
semilogy(loss_GD,'r-','LineWidth',3);
hold on
semilogy(loss_cyclic_IAG,'c-','LineWidth',3);
hold on
semilogy(loss_R_IAG,'g--','LineWidth',3);
hold on
semilogy(loss_LAG_PS,'r--','LineWidth',3);
hold on
semilogy(loss_LAG_WK,'m-','LineWidth',3);
hold on
semilogy(loss_DGD,'y-','LineWidth',3);
hold on
semilogy(loss_dualAvg,'b-','LineWidth',3);
hold on
semilogy(loss_GADMM_rho0002,'k-','LineWidth',3);
hold on
semilogy(loss_GADMM_rho0003,'b--','LineWidth',3);
hold on
% semilogy(loss_GADMM_rho0007,'b--','LineWidth',3);
% hold on
%semilogy(loss_GADMM_rho0009,'b--','LineWidth',3);
%hold on
xlabel({'Number of Iterations';'(a)'},'fontsize',16,'fontname','Times New Roman')
ylabel('Objective Error','fontsize',16,'fontname','Times New Roman')
legend('GD','cyclic-IAG','R-IAG','LAG-PS','LAG-WK','DGD','dualAvg', 'GADMM, \rho=2E-3'...
,'GADMM, \rho=3E-3');
%ylim([10^-4 10^3])
%xlim([10 30000])
ylim([10^-4 10^3])
set(gca,'fontsize',14,'fontweight','bold');
subplot(1,3,2);
semilogy(cumulative_com_GD(1:length(loss_GD)), loss_GD,'r-','LineWidth',3);
hold on
semilogy(cumulative_com_LAG_PS, loss_LAG_PS,'r--','LineWidth',3);
hold on
semilogy(cumulative_com_LAG_WK, loss_LAG_WK,'m-','LineWidth',3);
hold on
semilogy(cumulative_com_DGD, loss_DGD,'y-','LineWidth',3);
hold on
semilogy(cumulative_com_dualAvg, loss_dualAvg,'b-','LineWidth',3);
hold on
semilogy(cumulative_com_GADMM_rho0002,loss_GADMM_rho0002, 'k-','LineWidth',3);
hold on
semilogy(cumulative_com_GADMM_rho0003,loss_GADMM_rho0003, 'b--','LineWidth',3);
hold on
% semilogy(cumulative_com_GADMM_rho0007,loss_GADMM_rho0007, 'b--','LineWidth',3);
% hold on
%semilogy(cumulative_com_GADMM_rho0009,loss_GADMM_rho0009, 'b-','LineWidth',3);
%hold on
xlabel({'Cumulative Communication Cost';'(b)'},'fontsize',16,'fontname','Times New Roman')
ylabel('Objective Error','fontsize',16,'fontname','Times New Roman')
legend('GD','LAG-PS','LAG-WK','DGD','dualAvg', 'GADMM, \rho=2E-3'...
,'GADMM, \rho=3E-3');
%ylim([10^-4 10^3])
xlim([0 1E6])
ylim([10^-4 10^3])
set(gca,'fontsize',14,'fontweight','bold');
subplot(1,3,3);
semilogy(time_GD, loss_GD,'r-','LineWidth',3);
hold on
semilogy(time_lagPS, loss_LAG_PS,'r--','LineWidth',3);
hold on
semilogy(time_lagWK, loss_LAG_WK,'m-','LineWidth',3);
hold on
semilogy(time_DGD, loss_DGD,'y-','LineWidth',3);
hold on
semilogy(dualAvg_time, loss_dualAvg,'b-','LineWidth',3);
hold on
semilogy(gadmm_time0002,loss_GADMM_rho0002, 'k-','LineWidth',3);
hold on
semilogy(gadmm_time0003,loss_GADMM_rho0003, 'b--','LineWidth',3);
hold on
% semilogy(gadmm_time0007,loss_GADMM_rho0007, 'b--','LineWidth',3);
% hold on
%semilogy(gadmm_time0009,loss_GADMM_rho0009, 'b-','LineWidth',3);
%hold on
xlabel({'Clock Time';'(b)'},'fontsize',16,'fontname','Times New Roman')
ylabel('Objective Error','fontsize',16,'fontname','Times New Roman')
legend('GD','LAG-PS','LAG-WK','DGD','dualAvg', 'GADMM, \rho=2E-3'...
,'GADMM, \rho=3E-3');
%ylim([10^-4 10^3])
xlim([0 1.5])
ylim([10^-4 10^3])
set(gca,'fontsize',14,'fontweight','bold');
figure(4);
semilogy(loss_GADMM_rho0002,'k-','LineWidth',3);
hold on
semilogy(loss_GADMM_rho0003,'b--','LineWidth',3);
hold on
% semilogy(loss_GADMM_rho0007,'b--','LineWidth',3);
% hold on
%semilogy(loss_GADMM_rho0009,'b-','LineWidth',3);
ylim([10^-4 10^1])
xlim([1 80])
set(gca,'fontsize',14,'fontweight','bold');
figure(5);
%semilogy(cumulative_com_LAG_WK, loss_LAG_WK,'m-','LineWidth',3);
%hold on
semilogy(cumulative_com_GADMM_rho0002,loss_GADMM_rho0002, 'k-','LineWidth',3);
hold on
semilogy(cumulative_com_GADMM_rho0003,loss_GADMM_rho0003, 'b--','LineWidth',3);
hold on
% semilogy(cumulative_com_GADMM_rho0007,loss_GADMM_rho0007, 'b--','LineWidth',3);
% hold on
%semilogy(cumulative_com_GADMM_rho0009,loss_GADMM_rho0009, 'b-','LineWidth',3);
%hold on
ylim([10^-4 10^1])
xlim([1 2000])
set(gca,'fontsize',14,'fontweight','bold');