namespace regression

// namespaces

namespace xf::data_analytics::regression::internal

// classes

template <
    typename MType,
    int D,
    int DDepth,
    RAMType RAMWeight,
    RAMType RAMIntercept
    >
class LASSORegressionPredict

template <
    typename MType,
    int D,
    int DDepth,
    RAMType RAMWeight,
    RAMType RAMIntercept
    >
class linearLeastSquareRegressionPredict

template <
    typename MType,
    int D,
    int DDepth,
    RAMType RAMWeight,
    RAMType RAMIntercept
    >
class ridgeRegressionPredict

decisionTreePredict

#include "xf_data_analytics/regression/decision_tree_predict.hpp"

template <
    typename MType,
    unsigned int WD,
    unsigned int MAX_FEA_NUM,
    unsigned int MAX_TREE_DEPTH = 10
    >
void decisionTreePredict (
    hls::stream <ap_uint <WD>> dstrm_batch [MAX_FEA_NUM],
    hls::stream <bool>& estrm_batch,
    hls::stream <ap_uint <512>>& treeStrm,
    hls::stream <bool>& treeTag,
    hls::stream <MType>& predictionsStrm,
    hls::stream <bool>& predictionsTag
    )

decisionTreePredict, Top function of Decision Tree Predict.

This function first loads decision tree (the corresponding function : getTree) from treeStrm Then, read sample one by one from dstrm_batch, and output its category id into predictionsStrm streams

Note that the treeStrm is a 512-bit stream, and each 512 bits include two nodes. In each 512-bit confirm the range(0,71) is node[i].nodeInfo and range(256,327) is node[i+1].nodeInfo the range(72,135) is node[i].regValue and range(328,391) is node[i+1].regValue the range(192,255) is node[i].threshold and range(448,511) is node[i+1].threshold For detailed info of NodeR struct, can refer “decision_tree_L1.hpp” Samples in input sample stream should be converted into ap_uint<WD> from MType

Parameters:

MType	The data type of sample
WD	The width of data type MType, can get by sizeof(MType)
MAX_FEA_NUM	The max feature num function can support
MAX_TREE_DEPTH	The max tree depth function can support
dstrm_batch	Input data streams of ap_uint<WD>
estrm_batch	End flag stream for input data
treeStrm	Decision tree streams
treeTag	End flag stream for decision tree nodes
predictionsStrm	Output regression value streams
predictionsTagStrm	End flag stream for output