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[TRAVIS] cleanup travis script

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This commit is contained in:
tqchen
2016-01-14 17:08:41 -08:00
parent fd173e260f
commit 634db18a0f
25 changed files with 2558 additions and 171 deletions
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17
include/xgboost/c_api.h
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@@ -169,7 +169,8 @@ XGB_DLL int XGDMatrixGetFloatInfo(const DMatrixHandle handle,
* \brief get uint32 info vector from matrix
* \param handle a instance of data matrix
* \param field field name
* \param out_ptr pointer to the result
* \param out_len The length of the field.
* \param out_dptr pointer to the result
* \return 0 when success, -1 when failure happens
*/
XGB_DLL int XGDMatrixGetUIntInfo(const DMatrixHandle handle,
@@ -177,8 +178,9 @@ XGB_DLL int XGDMatrixGetUIntInfo(const DMatrixHandle handle,
bst_ulong* out_len,
const unsigned **out_dptr);
/*!
* \brief get number of rows
* \brief get number of rows.
* \param handle the handle to the DMatrix
* \param out The address to hold number of rows.
* \return 0 when success, -1 when failure happens
*/
XGB_DLL int XGDMatrixNumRow(DMatrixHandle handle,
@@ -186,6 +188,7 @@ XGB_DLL int XGDMatrixNumRow(DMatrixHandle handle,
/*!
* \brief get number of columns
* \param handle the handle to the DMatrix
* \param out The output of number of columns
* \return 0 when success, -1 when failure happens
*/
XGB_DLL int XGDMatrixNumCol(DMatrixHandle handle,
@@ -212,7 +215,7 @@ XGB_DLL int XGBoosterFree(BoosterHandle handle);
* \brief set parameters
* \param handle handle
* \param name parameter name
* \param val value of parameter
* \param value value of parameter
* \return 0 when success, -1 when failure happens
*/
XGB_DLL int XGBoosterSetParam(BoosterHandle handle,
@@ -335,11 +338,11 @@ XGB_DLL int XGBoosterDumpModel(BoosterHandle handle,
* \brief dump model, return array of strings representing model dump
* \param handle handle
* \param fnum number of features
* \param fnum names of features
* \param fnum types of features
* \param fname names of features
* \param ftype types of features
* \param with_stats whether to dump with statistics
* \param out_len length of output array
* \param out_dump_array pointer to hold representing dump of each model
* \param out_models pointer to hold representing dump of each model
* \return 0 when success, -1 when failure happens
*/
XGB_DLL int XGBoosterDumpModelWithFeatures(BoosterHandle handle,
@@ -347,7 +350,7 @@ XGB_DLL int XGBoosterDumpModelWithFeatures(BoosterHandle handle,
const char **fname,
const char **ftype,
int with_stats,
bst_ulong *len,
bst_ulong *out_len,
const char ***out_models);
#endif // XGBOOST_C_API_H_

1
include/xgboost/data.h
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@@ -262,7 +262,6 @@ class DMatrix {
/*!
* \brief create a new DMatrix, by wrapping a row_iterator, and meta info.
* \param source The source iterator of the data, the create function takes ownership of the source.
* \param info The meta information in the DMatrix, need to move ownership to DMatrix.
* \param cache_prefix The path to prefix of temporary cache file of the DMatrix when used in external memory mode.
* This can be nullptr for common cases, and in-memory mode will be used.
* \return a Created DMatrix.

7
include/xgboost/gbm.h
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@@ -70,7 +70,6 @@ class GradientBooster {
* \param p_fmat feature matrix that provide access to features
* \param buffer_offset buffer index offset of these instances, if equals -1
* this means we do not have buffer index allocated to the gbm
* \param info meta information about training
* \param in_gpair address of the gradient pair statistics of the data
* the booster may change content of gpair
*/
@@ -79,12 +78,11 @@ class GradientBooster {
std::vector<bst_gpair>* in_gpair) = 0;
/*!
* \brief generate predictions for given feature matrix
* \param p_fmat feature matrix
* \param dmat feature matrix
* \param buffer_offset buffer index offset of these instances, if equals -1
* this means we do not have buffer index allocated to the gbm
* a buffer index is assigned to each instance that requires repeative prediction
* the size of buffer is set by convention using GradientBooster.ResetPredBuffer(size);
* \param info extra side information that may be needed for prediction
* \param out_preds output vector to hold the predictions
* \param ntree_limit limit the number of trees used in prediction, when it equals 0, this means
* we do not limit number of trees, this parameter is only valid for gbtree, but not for gblinear
@@ -128,8 +126,9 @@ class GradientBooster {
*/
virtual std::vector<std::string> Dump2Text(const FeatureMap& fmap, int option) const = 0;
/*!
* \breif create a gradient booster from given name
* \brief create a gradient booster from given name
* \param name name of gradient booster
* \return The created booster.
*/
static GradientBooster* Create(const std::string& name);
};

2
include/xgboost/metric.h
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@@ -39,7 +39,7 @@ class Metric {
/*!
* \brief create a metric according to name.
* \param name name of the metric.
* name can be in form metric@param
* name can be in form metric[@]param
* and the name will be matched in the registry.
* \return the created metric.
*/

14
include/xgboost/tree_model.h
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@@ -105,11 +105,11 @@ class TreeModel {
inline bool is_leaf() const {
return cleft_ == -1;
}
/*! \brief get leaf value of leaf node */
/*! \return get leaf value of leaf node */
inline float leaf_value() const {
return (this->info_).leaf_value;
}
/*! \brief get split condition of the node */
/*! \return get split condition of the node */
inline TSplitCond split_cond() const {
return (this->info_).split_cond;
}
@@ -131,7 +131,7 @@ class TreeModel {
}
/*!
* \brief set the right child
* \param nide node id to right child
* \param nid node id to right child
*/
inline void set_right_child(int nid) {
this->cright_ = nid;
@@ -228,7 +228,7 @@ class TreeModel {
/*!
* \brief change a non leaf node to a leaf node, delete its children
* \param rid node id of the node
* \param new leaf value
* \param value new leaf value
*/
inline void ChangeToLeaf(int rid, float value) {
CHECK(nodes[nodes[rid].cleft() ].is_leaf());
@@ -240,7 +240,7 @@ class TreeModel {
/*!
* \brief collapse a non leaf node to a leaf node, delete its children
* \param rid node id of the node
* \param new leaf value
* \param value new leaf value
*/
inline void CollapseToLeaf(int rid, float value) {
if (nodes[rid].is_leaf()) return;
@@ -350,7 +350,7 @@ class TreeModel {
}
/*!
* \brief only add a right child to a leaf node
* \param node id to add right child
* \param nid node id to add right child
*/
inline void AddRightChild(int nid) {
int pright = this->AllocNode();
@@ -467,7 +467,7 @@ class RegTree: public TreeModel<bst_float, RTreeNodeStat> {
inline int GetLeafIndex(const FVec& feat, unsigned root_id = 0) const;
/*!
* \brief get the prediction of regression tree, only accepts dense feature vector
* \param feats dense feature vector, if the feature is missing the field is set to NaN
* \param feat dense feature vector, if the feature is missing the field is set to NaN
* \param root_id starting root index of the instance
* \return the leaf index of the given feature
*/

2
include/xgboost/tree_updater.h
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@@ -32,7 +32,7 @@ class TreeUpdater {
/*!
* \brief perform update to the tree models
* \param gpair the gradient pair statistics of the data
* \param dmat The data matrix passed to the updater.
* \param data The data matrix passed to the updater.
* \param trees references the trees to be updated, updater will change the content of trees
* note: all the trees in the vector are updated, with the same statistics,
* but maybe different random seeds, usually one tree is passed in at a time,