One studies the almost sure limiting behavior and convergence rate of the kernel regression estimator. By the local polynomial fit method of Fan and Gijbels [2] to construct a general weight kernel regression estimator. In this paper, the almost sure limiting behavior and the convergence rate of the proposed estimator are given. As the domain of density is compactly supported, the proposed estimator can be improved the problem of boundary effects, this is, it does not also need to adjust the boundary regions. Besides, the proposed estimator can also improve the bias and its convergent rate is achieved at (The equation is abbreviated), for all x∈[a, b] or real line and p≥1.