Commit | Line | Data |
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a961f8a1 BA |
1 | #include <math.h> |
2 | #include <stdlib.h> | |
3 | ||
4 | void ew_predict_noNA(double* X, double* Y, int* n_, int* K_, double* alpha_, int* grad_, double* weight) | |
5 | { | |
6 | int K = *K_; | |
7 | int n = *n_; | |
8 | double alpha = *alpha_; | |
9 | int grad = *grad_; | |
10 | ||
11 | //at least two experts to combine: various inits | |
12 | double invMaxError = 1. / 50; //TODO: magic number | |
13 | double logK = log(K); | |
14 | double initWeight = 1. / K; | |
15 | for (int i=0; i<K; i++) | |
16 | weight[i] = initWeight; | |
17 | double* error = (double*)malloc(K*sizeof(double)); | |
18 | double* cumError = (double*)calloc(K, sizeof(double)); | |
19 | ||
20 | //start main loop | |
21 | for (int t=0; t<n; t++ < n) | |
22 | { | |
23 | if (grad) | |
24 | { | |
25 | double hatY = 0.; | |
26 | for (int i=0; i<K; i++) | |
27 | hatY += X[t*K+i] * weight[i]; | |
28 | for (int i=0; i<K; i++) | |
29 | error[i] = 2. * (hatY - Y[t]) * X[t*K+i]; | |
30 | } | |
31 | else | |
32 | { | |
33 | for (int i=0; i<K; i++) | |
34 | { | |
35 | double delta = X[t*K+i] - Y[t]; | |
36 | error[i] = delta * delta; | |
37 | /* if ((X[t*K+i] <= 30 && Y[t] > 30) || (X[t*K+i] > 30 && Y[t] <= 30)) | |
38 | error[i] = 1.0; | |
39 | else | |
40 | error[i] = 0.0; | |
41 | */ | |
42 | } | |
43 | } | |
44 | for (int i=0; i<K; i++) | |
45 | cumError[i] += error[i]; | |
46 | ||
47 | if (t < n-1 && !grad) | |
48 | { | |
49 | //weight update is useless | |
50 | continue; | |
51 | } | |
52 | ||
53 | //double eta = invMaxError * sqrt(8*logK/(t+1)); //TODO: good formula ? | |
54 | double eta = invMaxError * 1. / (t+1); //TODO: good formula ? | |
55 | for (int i=0; i<K; i++) | |
56 | weight[i] = exp(-eta * cumError[i]); | |
57 | double sumWeight = 0.0; | |
58 | for (int i=0; i<K; i++) | |
59 | sumWeight += weight[i]; | |
60 | for (int i=0; i<K; i++) | |
61 | weight[i] /= sumWeight; | |
62 | //redistribute weights if alpha > 0 (all weights are 0 or more, sum > 0) | |
63 | for (int i=0; i<K; i++) | |
64 | weight[i] = (1. - alpha) * weight[i] + alpha/K; | |
65 | } | |
66 | ||
67 | free(error); | |
68 | free(cumError); | |
69 | } |