linear least square regression predict
Parameters:
| MType | datatype of regression, support double and float |
| D | Number of features that processed each cycle |
| DDepth | DDepth * D is max feature numbers supported. |
| K | Number of weight vectors that processed each cycle |
| KDepth | KDepth * K is max weight vectors supported. |
| RAMWeight | Use which kind of RAM to store weight, could be LUTRAM, BRAM or URAM. |
| RAMIntercept | Use which kind of RAM to store intercept, could be LUTRAM, BRAM or URAM. |
template < typename MType, int D, int DDepth, int K, int KDepth, RAMType RAMWeight, RAMType RAMIntercept > class logisticRegressionPredict // fields static const int marginDepth sl2 <MType, D, DDepth, K, KDepth,&funcMul <MType>,&funcSum <MType>,&funcAssign <MType>, AdditionLatency <MType>::value, RAMWeight, RAMIntercept> marginProcessor pickMaxProcess <MType, K> pickProcessor