نتایج جستجو برای: mean squared error mse and root mean squared error rmse if me and mse are closer to zero
تعداد نتایج: 18449156 فیلتر نتایج به سال:
this study aimed at examining the effects of iranian efl learners’ anxiety, ambiguity tolerance, and gender on their preferences for corrective feedback (cf, henceforth). the effects were sought with regard to the necessity, frequency, and timing of cf, types of errors that need to be treated, types of cf, and choice of correctors. seventy-five iranian efl students, twenty-eight males and forty...
This paper presents a density estimator based upon a histogram computed on a fuzzy partition. We prove the consistency of this estimator in the Mean Squared Error (MSE). We give the optimal bin width of the estimator which minimizes the Asymptotic Integrated Mean Squared Error (AIMSE). c © 2008 Elsevier B.V. All rights reserved.
Error measures for the evaluation of forecasts are usually based on the size of the forecast errors. Common measures are e.g. the Mean Squared Error (MSE), the Mean Absolute Deviation (MAD) or the Mean Absolute Percentage Error (MAPE). Alternative measures for the comparison of forecasts are turning points or hits-and-misses, where an indicator loss function is used to decide, if a forecast is ...
in the area of vocabulary teaching and learning although much research has been done, only some of it has led to effective techniques of vocabulary teaching and many language learners still have problem learning vocabulary. the urge behind this study was to investigate three methods of teaching words. the first one was teaching words in context based on a traditional method of teaching that is,...
Abstract This note discusses some issues related to bandwidth selection based on moment expansions of the mean squared error (MSE) of the regression quantile estimator. We use higher order expansions to provide a way to distinguish among asymptotically equivalent nonparametric estimators. We derive approximations to the (standardized) MSE of the covariance matrix estimation. This facilitates a ...
This paper develops ensemble machine learning models (XGBoost, Gradient Boosting, and AdaBoost in addition to Random Forest) for predicting stock returns of Indian banks using technical indicators. These indicators are based on three broad categories analysis: Price, Volume, Turnover. Various error metrics like Mean Absolute Error (MAE), Squared (MSE), Percentage (MAPE), Root-Mean-Squared-Error...
In this paper, we propose a new ridge-type estimator called the new mixed ridge estimator (NMRE) by unifying the sample and prior information in linear measurement error model with additional stochastic linear restrictions. The new estimator is a generalization of the mixed estimator (ME) and ridge estimator (RE). The performances of this new estimator and mixed ridge estimator (MRE) against th...
one of the most important number sequences in mathematics is fibonacci sequence. fibonacci sequence except for mathematics is applied to other branches of science such as physics and arts. in fact, between anesthetics and this sequence there exists a wonderful relation. fibonacci sequence has an importance characteristic which is the golden number. in this thesis, the golden number is observed ...
Consistent reconstruction is a method for producing an estimate x̃ ∈ R of a signal x ∈ R if one is given a collection ofN noisy linear measurements qn = 〈x, φn〉+ǫn, 1 ≤ n ≤ N , that have been corrupted by i.i.d. uniform noise {ǫn}n=1. We prove mean squared error bounds for consistent reconstruction when the measurement vectors {φn}n=1 ⊂ R are drawn independently at random from a suitable distrib...
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