- 1. Jubatus Preferred Infrastructure (@unnonouno)
2014/06/06Machine Learning Casual Talks@Cookpad
2. @unnonouno l () Preferred Infrastructure l Jubatus l l 2 3. l
Jubatus l Jubatus 3 4. Jubatus (http://jubat.us/) l l l l 4 5.
Jubatus 5 msgpack-rpc 6. l l msgpack-rpc l l l l l l l l
jubatus_core 6 7. l l l l l l 7 8. l l l l l l 8 9. l l l l l l 9
10. 10 11. 3 l l l 11 12. 12(1, 1)(-1, -1)1 13. l Perceptron l 95%
l Passive Aggressive l 97 l Confidence Weighted l 98% l AROW l 98%
l NHERD l 70% 13 14. 14 15. 15 16. 2 1 70 16 17. Crammer
17initialize w, " for (x, y) in data:" #m = y (xw)" #if m < e:"
# #w := w + yx" # #update " l l e, , 18. 18 19. 19void
normal_herd::update( const common::sfv_t& sfv, float margin,
float variance, const string& pos_label, const string&
neg_label) { for (common::sfv_t::const_iterator it = sfv.begin();
it != sfv.end(); ++it) { // storage_->set2(feature, pos_label,
storage::val2_t(pos_val.v1 + (1.f - margin) * val_covariance_pos /
(val_covariance_pos * val + 1.f / C), 1.f / ((1.f / pos_val.v2) +
(2 * C + C * C * variance) * val * val))); if (neg_label != "") {
storage_->set2(feature, neg_label, storage::val2_t(neg_val.v1 +
(1.f - margin) * val_covariance_neg / (val_covariance_neg * val +
1.f / C), 1.f / ((1.f / neg_val.v2) + (2 * C + C * C * variance) *
val * val))); } } } 20. l 1 l l l l 20 21. l l 21 22. 22 23. @@
-38,7 +38,7 @@ void PA::train(const sfv_t& sfv, const
string& label) {" if (sfv_norm == 0.f) {" return;" }" -
update_weight(sfv, loss / sfv_norm, label, incorrect_label);" +
update_weight(sfv, loss / (2 * sfv_norm), label, incorrect_label);"
}" " string PA::name() const { 23 24. l news20 l l l 24 25. l l l
25 26. -c l C l 26% svm-train" Usage: svm-train [options]
training_set_file [model_file]" options:" ..." -c cost : set the
parameter C of C-SVC, epsilon-SVR, and nu-SVR (default 1)" ... 27.
AROW 27 28. 12 28 29. AROW 29 30. AROW 30 31. r 31 32. l r l 32 33.
l 1/r l l 33 34. --- a/src/classifier/arow.cpp" +++
b/src/classifier/arow.cpp" @@ -40,7 +40,7 @@ void AROW::train(const
sfv_t& sfv, const string& label){" if (margin >= 1.f) {"
return;" }" - float beta = 1.f / (variance + config.C);" + float
beta = 1.f / (variance + 1.f / config.C);" float alpha = (1.f -
margin) * beta; // max(0, 1- margin) = 1-margin" update(sfv, alpha,
beta, label, incorrect_label);" } 34 35. 35 36. l l (2)r l 36 37. 1
l l l l 37 38. CoreSet l k-means l Jubatus 38 39. l K 396 40. l 1 2
40 41. l l l l 4113 42. l l l l l l l l l 42 43. 43 44. 44
