Missing value estimation for microarray expression data based on weighted regression 基因表達缺失值的加權回歸估計算法
Thirdly , a learning method based on locally weighted regression is proposed to forecast the motion of the ball , especially after the ball bump into wall ( 3 )提出一種基于局部加權回歸預測球運動軌跡的學習方法,尤其是球與邊界碰撞后的運動軌跡。
Results show that the proposed weighted regression calibration method is the most efficient and that the standard errors estimated using a bootstrap procedure are satisfactory 對于參數(shù)估計量的標準差,我們則是利用拔靴法來估計,其結果的表現(xiàn)也與模擬的標準差很接近。
Results show that the proposed weighted regression calibration method is the most efficient and that the standard errors estimated using a bootstrap procedure are satisfactory 對于參數(shù)估計量的標準差,我們則是利用拔靴法來估計,其結果的表現(xiàn)也與仿真的標準差很接近。
Firstly , it introduces the gradient boosting theory and the no weight regression algorithm based on this theory , then it presents the experimental results of a practical problem 首先對以損失函數(shù)梯度下降為原理的樣本無權值算法進行了闡述,并給出了一個實際問題的仿真結果。