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clean up warnings from msvc

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This commit is contained in:
Tianqi Chen
2014-08-25 11:01:21 -07:00
parent 4f0b0d2c88
commit ca0b008fb0
20 changed files with 217 additions and 46 deletions
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2
src/tree/param.h
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@@ -67,7 +67,7 @@ struct TrainParam{
if (!strcmp(name, "min_child_weight")) min_child_weight = static_cast<float>(atof(val));
if (!strcmp(name, "min_split_loss")) min_split_loss = static_cast<float>(atof(val));
if (!strcmp(name, "reg_lambda")) reg_lambda = static_cast<float>(atof(val));
if (!strcmp(name, "reg_method")) reg_method = static_cast<float>(atof(val));
if (!strcmp(name, "reg_method")) reg_method = atoi(val);
if (!strcmp(name, "subsample")) subsample = static_cast<float>(atof(val));
if (!strcmp(name, "colsample_bylevel")) colsample_bylevel = static_cast<float>(atof(val));
if (!strcmp(name, "colsample_bytree")) colsample_bytree = static_cast<float>(atof(val));

8
src/tree/updater_colmaker-inl.hpp
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@@ -203,8 +203,8 @@ class ColMaker: public IUpdater<FMatrix> {
}
// update node statistics
snode[nid].stats = stats;
snode[nid].root_gain = stats.CalcGain(param);
snode[nid].weight = stats.CalcWeight(param);
snode[nid].root_gain = static_cast<float>(stats.CalcGain(param));
snode[nid].weight = static_cast<float>(stats.CalcWeight(param));
}
}
/*! \brief update queue expand add in new leaves */
@@ -251,7 +251,7 @@ class ColMaker: public IUpdater<FMatrix> {
if (fabsf(fvalue - e.last_fvalue) > rt_2eps && e.stats.sum_hess >= param.min_child_weight) {
c.SetSubstract(snode[nid].stats, e.stats);
if (c.sum_hess >= param.min_child_weight) {
double loss_chg = e.stats.CalcGain(param) + c.CalcGain(param) - snode[nid].root_gain;
bst_float loss_chg = static_cast<bst_float>(e.stats.CalcGain(param) + c.CalcGain(param) - snode[nid].root_gain);
e.best.Update(loss_chg, fid, (fvalue + e.last_fvalue) * 0.5f, !is_forward_search);
}
}
@@ -266,7 +266,7 @@ class ColMaker: public IUpdater<FMatrix> {
ThreadEntry &e = temp[nid];
c.SetSubstract(snode[nid].stats, e.stats);
if (e.stats.sum_hess >= param.min_child_weight && c.sum_hess >= param.min_child_weight) {
const double loss_chg = e.stats.CalcGain(param) + c.CalcGain(param) - snode[nid].root_gain;
bst_float loss_chg = static_cast<bst_float>(e.stats.CalcGain(param) + c.CalcGain(param) - snode[nid].root_gain);
const float delta = is_forward_search ? rt_eps : -rt_eps;
e.best.Update(loss_chg, fid, e.last_fvalue + delta, !is_forward_search);
}

8
src/tree/updater_refresh-inl.hpp
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@@ -61,7 +61,7 @@ class TreeRefresher: public IUpdater<FMatrix> {
for (unsigned i = 0; i < nbatch; ++i) {
SparseBatch::Inst inst = batch[i];
const int tid = omp_get_thread_num();
const size_t ridx = batch.base_rowid + i;
const bst_uint ridx = static_cast<bst_uint>(batch.base_rowid + i);
RegTree::FVec &feats = fvec_temp[tid];
feats.Fill(inst);
for (size_t j = 0; j < trees.size(); ++j) {
@@ -112,16 +112,16 @@ class TreeRefresher: public IUpdater<FMatrix> {
inline void Refresh(const std::vector<TStats> &gstats,
int nid, RegTree *p_tree) {
RegTree &tree = *p_tree;
tree.stat(nid).base_weight = gstats[nid].CalcWeight(param);
tree.stat(nid).base_weight = static_cast<float>(gstats[nid].CalcWeight(param));
tree.stat(nid).sum_hess = static_cast<float>(gstats[nid].sum_hess);
gstats[nid].SetLeafVec(param, tree.leafvec(nid));
if (tree[nid].is_leaf()) {
tree[nid].set_leaf(tree.stat(nid).base_weight * param.learning_rate);
} else {
tree.stat(nid).loss_chg =
tree.stat(nid).loss_chg = static_cast<float>(
gstats[tree[nid].cleft()].CalcGain(param) +
gstats[tree[nid].cright()].CalcGain(param) -
gstats[nid].CalcGain(param);
gstats[nid].CalcGain(param));
this->Refresh(gstats, tree[nid].cleft(), p_tree);
this->Refresh(gstats, tree[nid].cright(), p_tree);
}