Question

1. What is a significant weakness of naïve models and why is this weakness significant?

2. What is the significance of the standard error of the estimate and the prediction confidence

interval?

Answer 1

1.

The independent attribute is the most significant weakness and something that requires additional effort in the calculation of outcome probabilites using the classical Bayes theorem. The implicit assumption is that all the attributes are mutually independent. This allows us to multiply the class conditional probabilities in order to compute the outcome probability. When it is known beforehand that a few of the attributes are correlated (for example, overcast conditions may be correlated to medium temperatures), it is easy to ignore one of the correlated attributes. However, it becomes very difficult if you do when you do not know which attributes are dependent on one another?

2.

The standard error of the estimate is a measure of the accuracy of predictions made with a regression line. A standard error is the standard deviation of the sampling distribution of a statistic. Standard error is a statistical term that measures the accuracy with which a sample represents a population. In statistics, a sample mean deviates from the actual mean of a population; this deviation is the standard error.The standard error is an important indicator of how precise an estimate of the population parameter the sample statistic is. Taken together with such measures as effect size, p-value and sample size, the effect size can be a useful tool to the researcher who seeks to understand the accuracy of statistics calculated on random samples.

A prediction interval is a type of confidence interval (CI) used with predictions in regression analysis. It is a range of values that predicts the value of a new observation, based on your existing model. Prediction and confidence intervals are often confused with each other. However, they are not quite the same thing. A confidence interval is a range of values associated with a population parameter while a prediction interval is where you expect a future value to fall.