In equation 12, you argue that you can calculate the conditional expectation term by simply calculating the function value using the actual instance values of the features in set S, and the expected ...

y <- (x-3)^3 + 3*x - .25*(x^2 * (x-3)) + rnorm(n=10000, mean=0, sd=3) dat <- data.frame(x = x, y = y) One of our most fundamental goals as data scientists is to produce predictions that are *good*. In ...

Abstract: Consider the problem of estimating the expectation of a non linear function of a conditional expectation. This function is allowed to be non-differentiable and discontinuous at a finite set ...

Abstract: Consider the problem of estimating the expectation of a non linear function of a conditional expectation. This function is allowed to be non-differentiable and discontinuous at a finite set ...

A double forecasting model based on conditional expectation was proposed through probability distribution of demand of automobile loan. The demand of automobile loan is the sum of all compound ...

Quantile regression(QR) fits a linear model for conditional quantiles, just as ordinary least squares (OLS) fits a linear model for conditional means. An attractive ...