Nonparametric Regularization of Decision Trees

ثبت نشده
چکیده

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Technical Note: Algorithms for Optimal Dyadic Decision Trees

A dynamic programming algorithm for constructing optimal dyadic decision trees was recently introduced, analyzed, and shown to be very effective for low dimensional data sets. This paper enhances and extends this algorithm by: introducing an adaptive grid search for the regularization parameter that guarantees optimal solutions for all relevant trees sizes, replacing the dynamic programming alg...

متن کامل

Regularized Policy Iteration with Nonparametric Function Spaces

We study two regularization-based approximate policy iteration algorithms, namely REGLSPI and REG-BRM, to solve reinforcement learning and planning problems in discounted Markov Decision Processes with large state and finite action spaces. The core of these algorithms are the regularized extensions of the Least-Squares Temporal Difference (LSTD) learning and Bellman Residual Minimization (BRM),...

متن کامل

Nonparametric learning and Regularization

Several nonparametric methods in a regression model are presented. First, the most classical ones: piecewise polynomial estimators, estimation with Spline bases, kernel estimators and projection estimators on orthonormal bases (such as Fourier or wavelet bases). Since these methods suffer from the curse of dimensionality, we also present Generalized Additive Models and CART regression models. T...

متن کامل

Nonparametric estimation of conditional quantiles using quantile regression trees

A nonparametric regression method that blends key features of piecewise polynomial quantile regression and tree-structured regression based on adaptive recursive partitioning of the covariate space is investigated. Unlike least squares regression trees, which concentrate on modeling the relationship between the response and the covariates at the center of the response distribution, our quantile...

متن کامل

Optimized Wavelet Packet decomposition based on Minimum Probability of Error Signal Representation

This work addresses the problem of optimal Wavelet packet (WP) filter bank decomposition based on the minimum probability of error signal representation (MPE-SR) principle. The problem is formulated as a complexity regularized optimization, where the tree-indexed structure of the WP family is explored to find conditions for reducing this problem to a type of minimum cost tree pruning, a method ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2000