Analyzing GeneXproTools Models Statistically

Correlation Coefficient

 The correlation coefficient Ci of an individual program i is evaluated by the equation: where Cov(T,P) is the covariance of the target and model outputs; and st and sp are the corresponding standard deviations, which are given by: where P(ij) is the value predicted by the individual program i for sample case j (out of n sample cases); Tj is the target value for sample case j; andandare given by the formulas: The correlation coefficient is confined to the range [-1, 1]. When Ci = 1, there is a perfect positive linear correlation between T and P, that is, they vary by the same amount. When Ci = -1, there is a perfect negative linear correlation between T and P, that is, they vary in opposite ways (when T increases, P decreases by the same amount). When Ci = 0, there is no correlation between T and P. Intermediate values describe partial correlations and the closer to 1 or -1 the better the model. To evaluate the correlation coefficient of your model both on the training and testing sets, you just have to go to the Results Panel after a run.
Home | Contents | Previous  | Next