Tuned nullmove search

Tuning was done with Bayesian optimisation and sequential use of gaussian process
regressor and gaussian process classifier. The latter is used in lieu of ordinal
categorical modelling. Details will be given in Fishcooking forum topic: https://groups.google.com/forum/?fromgroups=#!topic/fishcooking/b3uhBBJcJG4

STC:
LLR: 2.96 (-2.94,2.94) {-1.00,3.00}
Total: 10248 W: 2361 L: 2233 D: 5654
Ptnml(0-2): 191, 1153, 2303, 1276, 194
http://tests.stockfishchess.org/tests/view/5e0ba4159d3fbe26f672d4e6

LTC:
LLR: 2.94 (-2.94,2.94) {0.00,2.00}
Total: 16003 W: 2648 L: 2458 D: 10897
Ptnml(0-2): 121, 1595, 4394, 1718, 153
http://tests.stockfishchess.org/tests/view/5e0bb8519d3fbe26f672d4fd

Closes https://github.com/official-stockfish/Stockfish/pull/2468

Bench 4747984

src/search.cpp

@@ -825,10 +825,10 @@ namespace {
     // Step 9. Null move search with verification search (~40 Elo)
     if (   !PvNode
         && (ss-1)->currentMove != MOVE_NULL
-        && (ss-1)->statScore < 23405
+        && (ss-1)->statScore < 23397
         &&  eval >= beta
         &&  eval >= ss->staticEval
-        &&  ss->staticEval >= beta - 32 * depth + 317 - improving * 30
+        &&  ss->staticEval >= beta - 32 * depth + 292 - improving * 30
         && !excludedMove
         &&  pos.non_pawn_material(us)
         && (ss->ply >= thisThread->nmpMinPly || us != thisThread->nmpColor))